diff --git a/chatlas/__init__.py b/chatlas/__init__.py
index 60fe8658..f9fc6d54 100644
--- a/chatlas/__init__.py
+++ b/chatlas/__init__.py
@@ -38,7 +38,7 @@
 from ._stream_controller import StreamController
 from ._tokens import token_usage
 from ._tools import Tool, ToolBuiltIn, ToolRejectError
-from ._tools_builtin import tool_web_fetch, tool_web_search
+from ._tools_builtin import tool_code_execution, tool_web_fetch, tool_web_search
 from ._turn import AssistantTurn, SystemTurn, Turn, UserTurn
 
 try:
@@ -93,6 +93,7 @@
     "Tool",
     "ToolBuiltIn",
     "ToolRejectError",
+    "tool_code_execution",
     "tool_web_fetch",
     "tool_web_search",
     "Turn",
diff --git a/chatlas/_content.py b/chatlas/_content.py
index 2243343e..6deba7cd 100644
--- a/chatlas/_content.py
+++ b/chatlas/_content.py
@@ -146,6 +146,8 @@ def from_tool(cls, tool: "Tool | ToolBuiltIn") -> "ToolInfo":
     "web_search_results",
     "web_fetch_request",
     "web_fetch_results",
+    "code_execution_request",
+    "code_execution_result",
 ]
 """
 A discriminated union of all content types.
@@ -839,6 +841,74 @@ def __str__(self):
         return f"[web fetch result]: {self.url}"
 
 
+class ContentToolRequestCodeExecution(Content):
+    """
+    A code execution request from the model.
+
+    This content type represents the model's request to run code in a
+    sandboxed environment. It's automatically generated when a built-in code
+    execution tool is used.
+
+    Parameters
+    ----------
+    code
+        The code the model wants to run.
+    language
+        The programming language of `code`, if the provider reports it.
+    extra
+        The raw provider-specific response data.
+    """
+
+    code: str
+    language: Optional[str] = None
+    extra: Optional[dict[str, Any]] = None
+
+    content_type: ContentTypeEnum = "code_execution_request"
+
+    def __str__(self):
+        return f"[code execution request]:\n```\n{self.code}\n```"
+
+
+class ContentToolResponseCodeExecution(Content):
+    """
+    Code execution results from the model.
+
+    This content type represents the result of running code in a sandboxed
+    environment. It's automatically generated when a built-in code execution
+    tool returns results.
+
+    Only text output (stdout/stderr or each provider's equivalent) is
+    surfaced here. Files the code produced (e.g. plots, CSVs) aren't
+    downloaded or decoded -- their raw provider references are still
+    available via `extra`.
+
+    Parameters
+    ----------
+    output
+        The text output of the code (e.g. stdout).
+    error
+        The error output of the code (e.g. stderr), if any.
+    container_id
+        The id of the sandbox/container the code ran in, if the provider
+        exposes one. Used by `chatlas.Chat` to reuse the same sandbox across
+        turns for providers that support it (OpenAI, Anthropic).
+    extra
+        The raw provider-specific response data.
+    """
+
+    output: Optional[str] = None
+    error: Optional[str] = None
+    container_id: Optional[str] = None
+    extra: Optional[dict[str, Any]] = None
+
+    content_type: ContentTypeEnum = "code_execution_result"
+
+    def __str__(self):
+        if self.error:
+            return f"[code execution error]:\n```\n{self.error}\n```"
+        return f"[code execution result]:\n```\n{self.output or ''}\n```"
+
+
 ContentUnion = Union[
     ContentText,
     ContentImageRemote,
@@ -852,6 +922,8 @@ def __str__(self):
     ContentToolResponseSearch,
     ContentToolRequestFetch,
     ContentToolResponseFetch,
+    ContentToolRequestCodeExecution,
+    ContentToolResponseCodeExecution,
 ]
 
 
@@ -917,6 +989,10 @@ def create_content(data: dict[str, Any]) -> ContentUnion:
         return ContentToolRequestFetch.model_validate(data)
     elif ct == "web_fetch_results":
         return ContentToolResponseFetch.model_validate(data)
+    elif ct == "code_execution_request":
+        return ContentToolRequestCodeExecution.model_validate(data)
+    elif ct == "code_execution_result":
+        return ContentToolResponseCodeExecution.model_validate(data)
     else:
         raise ValueError(f"Unknown content type: {ct}")
 
diff --git a/chatlas/_provider_anthropic.py b/chatlas/_provider_anthropic.py
index 1892c230..3fdf9c43 100644
--- a/chatlas/_provider_anthropic.py
+++ b/chatlas/_provider_anthropic.py
@@ -28,8 +28,10 @@
     ContentThinking,
     ContentThinkingDelta,
     ContentToolRequest,
+    ContentToolRequestCodeExecution,
     ContentToolRequestFetch,
     ContentToolRequestSearch,
+    ContentToolResponseCodeExecution,
     ContentToolResponseFetch,
     ContentToolResponseSearch,
     ContentToolResult,
@@ -44,7 +46,12 @@
 )
 from ._tokens import get_price_info
 from ._tools import Tool, ToolBuiltIn, basemodel_to_param_schema
-from ._tools_builtin import ToolWebFetch, ToolWebSearch
+from ._tools_builtin import (
+    ToolCodeExecution,
+    ToolWebFetch,
+    ToolWebSearch,
+    last_code_execution_container_id,
+)
 from ._turn import AssistantTurn, FinishReason, SystemTurn, Turn, UserTurn, user_turn
 from ._utils import split_http_client_kwargs
 
@@ -492,6 +499,13 @@ def _chat_perform_args(
             **(kwargs or {}),
         }
 
+        if "container" not in kwargs_full and any(
+            isinstance(tool, ToolCodeExecution) for tool in tools.values()
+        ):
+            container_id = last_code_execution_container_id(turns)
+            if container_id is not None:
+                kwargs_full["container"] = container_id
+
         if data_model is not None and use_native:
             kwargs_full["output_config"] = output_config  # type: ignore[reportPossiblyUnbound]
         elif data_model is not None:
@@ -591,6 +605,10 @@ def stream_merge_chunks(self, completion, chunk):
             completion.stop_reason = chunk.delta.stop_reason
             completion.stop_sequence = chunk.delta.stop_sequence
             completion.usage.output_tokens = chunk.usage.output_tokens
+            # Anthropic only sends `container` (e.g. from the code execution
+            # tool) on the message_delta event, not message_start.
+            if chunk.delta.container is not None:
+                completion.container = chunk.delta.container
 
         return completion
 
@@ -716,9 +734,13 @@ def _as_message_params(self, turns: Sequence[Turn]) -> list["MessageParam"]:
             # https://docs.claude.com/en/docs/build-with-claude/prompt-caching#how-automatic-prefix-checking-works
             is_last_turn = i == len(turns) - 1
             if self._cache_control() and is_last_turn and len(content) > 0:
-                # Note: ThinkingBlockParam (i.e., type: "thinking") doesn't support cache_control
-                if content[-1].get("type") != "thinking":
-                    content[-1]["cache_control"] = self._cache_control()  # type: ignore
+                last_block = content[-1]
+                # Note: ThinkingBlockParam (i.e., type: "thinking") doesn't support
+                # cache_control. `last_block` can also be None for round-tripped
+                # server tool content missing `extra` (e.g. manually constructed
+                # in tests), in which case there's nothing to attach cache_control to.
+                if last_block is not None and last_block.get("type") != "thinking":
+                    last_block["cache_control"] = self._cache_control()  # type: ignore
 
             role = "user" if isinstance(turn, UserTurn) else "assistant"
             messages.append({"role": role, "content": content})
@@ -788,6 +810,8 @@ def _as_content_block(content: Content) -> "ContentBlockParam":
                 ContentToolResponseSearch,
                 ContentToolRequestFetch,
                 ContentToolResponseFetch,
+                ContentToolRequestCodeExecution,
+                ContentToolResponseCodeExecution,
             ),
         ):
             # extra contains the full original content block param
@@ -803,6 +827,9 @@ def _anthropic_tool_schema(tool: "Tool | ToolBuiltIn") -> "ToolUnionParam":
             # N.B. seems the return type here (BetaWebFetchTool20250910Param) is
             # not a member of ToolUnionParam since it's still in beta?
             return tool.get_definition("anthropic")  # type: ignore
+        if isinstance(tool, ToolCodeExecution):
+            # N.B. same beta-type situation as ToolWebFetch above.
+            return tool.get_definition("anthropic")  # type: ignore
         if isinstance(tool, ToolBuiltIn):
             return tool.definition  # type: ignore
 
@@ -907,6 +934,13 @@ def _as_turn(self, completion: Message, has_data_model=False) -> AssistantTurn:
                             extra=extra,
                         )
                     )
+                elif content.name == "code_execution":
+                    contents.append(
+                        ContentToolRequestCodeExecution(
+                            code=str(input_data.get("code", "")),
+                            extra=extra,
+                        )
+                    )
                 else:
                     raise ValueError(f"Unknown server tool: {content.name}")
             elif content.type == "web_search_tool_result":
@@ -954,6 +988,34 @@ def _as_turn(self, completion: Message, has_data_model=False) -> AssistantTurn:
                         extra=extra,
                     )
                 )
+            elif content.type == "code_execution_tool_result":
+                # https://docs.claude.com/en/docs/agents-and-tools/tool-use/code-execution-tool#result
+                result = content.content
+                if result.type == "code_execution_tool_result_error":
+                    output = None
+                    error = result.error_code
+                elif result.type == "code_execution_result":
+                    output = result.stdout or None
+                    error = result.stderr or None
+                else:
+                    # encrypted_code_execution_result: stdout isn't available in plaintext
+                    output = None
+                    error = result.stderr or None
+                extra = {
+                    "type": content.type,
+                    "tool_use_id": content.tool_use_id,
+                    "content": result.model_dump(exclude_none=True),
+                }
+                contents.append(
+                    ContentToolResponseCodeExecution(
+                        output=output,
+                        error=error,
+                        container_id=completion.container.id
+                        if completion.container
+                        else None,
+                        extra=extra,
+                    )
+                )
 
         return AssistantTurn(
             contents,
diff --git a/chatlas/_provider_google.py b/chatlas/_provider_google.py
index bdafdc15..a9af587b 100644
--- a/chatlas/_provider_google.py
+++ b/chatlas/_provider_google.py
@@ -19,6 +19,8 @@
     ContentThinking,
     ContentThinkingDelta,
     ContentToolRequest,
+    ContentToolRequestCodeExecution,
+    ContentToolResponseCodeExecution,
     ContentToolResult,
 )
 from ._logging import log_model_default
@@ -32,7 +34,7 @@
 )
 from ._tokens import get_price_info
 from ._tools import Tool, ToolBuiltIn
-from ._tools_builtin import ToolWebFetch, ToolWebSearch
+from ._tools_builtin import ToolCodeExecution, ToolWebFetch, ToolWebSearch
 from ._turn import AssistantTurn, FinishReason, SystemTurn, Turn, UserTurn, user_turn
 
 if TYPE_CHECKING:
@@ -398,6 +400,9 @@ def _chat_perform_args(
                 elif isinstance(tool, ToolWebFetch):
                     gtool = GoogleTool(url_context=tool.get_definition("google"))
                     google_tools.append(gtool)
+                elif isinstance(tool, ToolCodeExecution):
+                    gtool = GoogleTool(code_execution=tool.get_definition("google"))
+                    google_tools.append(gtool)
                 elif isinstance(tool, ToolBuiltIn):
                     gtool = GoogleTool.model_validate(tool.definition)
                     google_tools.append(gtool)
@@ -618,6 +623,26 @@ def _as_part_type(self, content: Content) -> "Part":
                     response=resp,
                 )
             )
+        elif isinstance(content, ContentToolRequestCodeExecution):
+            from google.genai.types import ExecutableCode, Language
+
+            return Part(
+                executable_code=ExecutableCode(
+                    code=content.code,
+                    language=Language.PYTHON,
+                )
+            )
+        elif isinstance(content, ContentToolResponseCodeExecution):
+            from google.genai.types import CodeExecutionResult, Outcome
+
+            return Part(
+                code_execution_result=CodeExecutionResult(
+                    outcome=Outcome.OUTCOME_FAILED
+                    if content.error
+                    else Outcome.OUTCOME_OK,
+                    output=content.error or content.output,
+                )
+            )
         raise ValueError(f"Unknown content type: {type(content)}")
 
     def _as_turn(
@@ -695,6 +720,28 @@ def _as_turn(
                             image_content_type=mime_type,  # type: ignore
                         )
                     )
+            executable_code = part.get("executable_code")
+            if executable_code:
+                code = executable_code.get("code")
+                if code:
+                    contents.append(
+                        ContentToolRequestCodeExecution(
+                            code=code,
+                            language=executable_code.get("language"),
+                            extra=dict(executable_code),
+                        )
+                    )
+            code_execution_result = part.get("code_execution_result")
+            if code_execution_result:
+                outcome = code_execution_result.get("outcome")
+                output = code_execution_result.get("output")
+                contents.append(
+                    ContentToolResponseCodeExecution(
+                        output=output if outcome == "OUTCOME_OK" else None,
+                        error=output if outcome != "OUTCOME_OK" else None,
+                        extra=dict(code_execution_result),
+                    )
+                )
 
         if isinstance(finish_reason, FinishReason):
             finish_reason = finish_reason.name
diff --git a/chatlas/_provider_openai.py b/chatlas/_provider_openai.py
index 28c402cb..605a606c 100644
--- a/chatlas/_provider_openai.py
+++ b/chatlas/_provider_openai.py
@@ -20,7 +20,9 @@
     ContentThinking,
     ContentThinkingDelta,
     ContentToolRequest,
+    ContentToolRequestCodeExecution,
     ContentToolRequestSearch,
+    ContentToolResponseCodeExecution,
     ContentToolResult,
 )
 from ._logging import log_model_default
@@ -28,7 +30,12 @@
 from ._provider_openai_completions import load_tool_request_args
 from ._provider_openai_generic import BatchResult, OpenAIAbstractProvider
 from ._tools import Tool, ToolBuiltIn, basemodel_to_param_schema
-from ._tools_builtin import ToolWebFetch, ToolWebSearch
+from ._tools_builtin import (
+    ToolCodeExecution,
+    ToolWebFetch,
+    ToolWebSearch,
+    last_code_execution_container_id,
+)
 from ._turn import AssistantTurn, FinishReason, Turn
 
 if TYPE_CHECKING:
@@ -272,6 +279,11 @@ def _chat_perform_args(
                     "Consider using the MCP Fetch server instead via chat.register_mcp_tools_stdio_async(). "
                     "See help(tool_web_fetch) for details."
                 )
+            elif isinstance(tool, ToolCodeExecution):
+                container_id = last_code_execution_container_id(turns)
+                tool_params.append(
+                    tool.get_definition("openai", container_id=container_id)
+                )
             elif isinstance(tool, ToolBuiltIn):
                 tool_params.append(cast("ToolParam", tool.definition))
             else:
@@ -465,6 +477,23 @@ def _response_as_turn(completion: Response, has_data_model: bool) -> AssistantTu
                     )
                 )
 
+            elif output.type == "code_interpreter_call":
+                # https://platform.openai.com/docs/guides/tools-code-interpreter#understanding-code-interpreter-output
+                contents.append(
+                    ContentToolRequestCodeExecution(
+                        code=output.code or "",
+                        extra=output.model_dump(),
+                    )
+                )
+                logs = [o.logs for o in (output.outputs or []) if o.type == "logs"]
+                contents.append(
+                    ContentToolResponseCodeExecution(
+                        output="\n".join(logs) or None,
+                        container_id=output.container_id,
+                        extra=output.model_dump(),
+                    )
+                )
+
             else:
                 raise ValueError(f"Unknown output type: {output.type}")
 
@@ -487,7 +516,11 @@ def _response_as_turn(completion: Response, has_data_model: bool) -> AssistantTu
     def _turns_as_inputs(self, turns: list[Turn]) -> "list[ResponseInputItemParam]":
         res: "list[ResponseInputItemParam]" = []
         for turn in turns:
-            res.extend([as_input_param(x, turn.role) for x in turn.contents])
+            res.extend(
+                x
+                for x in (as_input_param(c, turn.role) for c in turn.contents)
+                if x is not None
+            )
         return res
 
     def translate_model_params(self, params: StandardModelParams) -> "SubmitInputArgs":
@@ -525,7 +558,9 @@ def _batch_endpoint():
         return "/v1/responses"
 
 
-def as_input_param(content: Content, role: Role) -> "ResponseInputItemParam":
+def as_input_param(
+    content: Content, role: Role
+) -> "Optional[ResponseInputItemParam]":
     if isinstance(content, ContentText):
         if role == "assistant":
             # OpenAI's type for this value (ResponseOutputMessageParam) currently has a bunch
@@ -598,6 +633,13 @@ def as_input_param(content: Content, role: Role) -> "ResponseInputItemParam":
         }
     elif isinstance(content, ContentToolRequestSearch):
         return cast("ResponseInputItemParam", content.extra)
+    elif isinstance(content, ContentToolRequestCodeExecution):
+        return cast("ResponseInputItemParam", content.extra)
+    elif isinstance(content, ContentToolResponseCodeExecution):
+        # OpenAI bundles code + result into a single code_interpreter_call
+        # item, already captured by the paired
+        # ContentToolRequestCodeExecution's extra above.
+        return None
     else:
         raise ValueError(f"Unsupported content type: {type(content)}")
 
diff --git a/chatlas/_tools_builtin.py b/chatlas/_tools_builtin.py
index 356a35bb..852a4baa 100644
--- a/chatlas/_tools_builtin.py
+++ b/chatlas/_tools_builtin.py
@@ -1,22 +1,26 @@
 """
-Built-in provider tools for web search and fetch.
+Built-in provider tools for web search, web fetch, and code execution.
 
 These classes provide a provider-agnostic way to configure built-in tools
-like web search and URL fetching. Each provider translates these configurations
-into their specific API format.
+like web search, URL fetching, and code execution. Each provider translates
+these configurations into their specific API format.
 """
 
 from __future__ import annotations
 
 import warnings
-from typing import TYPE_CHECKING, Literal, Optional, overload
+from typing import TYPE_CHECKING, Literal, Optional, Sequence, overload
 
-from ._content import ToolAnnotations
+from ._content import ContentToolResponseCodeExecution, ToolAnnotations
 from ._tools import ToolBuiltIn
+from ._turn import AssistantTurn, Turn
 
 if TYPE_CHECKING:
     from anthropic.types import WebSearchTool20250305Param
-    from anthropic.types.beta import BetaWebFetchTool20250910Param
+    from anthropic.types.beta import (
+        BetaCodeExecutionTool20250522Param,
+        BetaWebFetchTool20250910Param,
+    )
     from anthropic.types.beta.beta_citations_config_param import (
         BetaCitationsConfigParam,
     )
@@ -29,7 +33,9 @@
         PhishBlockThreshold,
         UrlContext,
     )
+    from google.genai.types import ToolCodeExecution as GoogleToolCodeExecution
     from openai.types.responses import WebSearchToolParam
+    from openai.types.responses.tool_param import CodeInterpreter
 
     from ._typing_extensions import TypedDict
 
@@ -49,8 +55,10 @@ class UserLocation(TypedDict, total=False):
 __all__ = (
     "tool_web_search",
     "tool_web_fetch",
+    "tool_code_execution",
     "ToolWebSearch",
     "ToolWebFetch",
+    "ToolCodeExecution",
 )
 
 
@@ -643,3 +651,189 @@ async def main():
         blocked_domains=blocked_domains,
         max_uses=max_uses,
     )
+
+
+class ToolCodeExecution(ToolBuiltIn):
+    """
+    A provider-agnostic code execution tool configuration.
+
+    This class stores configuration for server-side code execution
+    functionality. Each provider translates this configuration into their
+    specific API format.
+    """
+
+    def __init__(self):
+        _annotations: ToolAnnotations = {
+            "title": "Code execution",
+            "readOnlyHint": False,
+            "openWorldHint": False,
+        }
+        super().__init__(
+            name="code_execution",
+            definition={},
+            description="Execute code in a sandboxed environment.",
+            annotations=_annotations,
+        )
+
+    @overload
+    def get_definition(
+        self,
+        provider_name: Literal["openai"],
+        *,
+        container_id: Optional[str] = None,
+    ) -> "CodeInterpreter": ...
+
+    @overload
+    def get_definition(
+        self,
+        provider_name: Literal["anthropic"],
+    ) -> "BetaCodeExecutionTool20250522Param": ...
+
+    @overload
+    def get_definition(
+        self,
+        provider_name: Literal["google"],
+    ) -> "GoogleToolCodeExecution": ...
+
+    def get_definition(
+        self,
+        provider_name: Literal["openai", "anthropic", "google"],
+        *,
+        # OpenAI-specific
+        container_id: Optional[str] = None,
+    ) -> (
+        "CodeInterpreter | BetaCodeExecutionTool20250522Param | GoogleToolCodeExecution"
+    ):
+        """
+        Get the provider-specific tool definition.
+
+        Parameters
+        ----------
+        provider_name
+            The name of the provider ('openai', 'anthropic', or 'google').
+        container_id
+            OpenAI only. Reuse an existing sandbox container instead of
+            starting a fresh one. `chatlas.Chat` sets this automatically
+            from prior turns; you shouldn't need to pass it yourself.
+
+        Returns
+        -------
+        :
+            The provider-specific tool definition.
+        """
+        if provider_name == "openai":
+            return self._openai_definition(container_id=container_id)
+        elif provider_name == "anthropic":
+            return self._anthropic_definition()
+        elif provider_name == "google":
+            return self._google_definition()
+        else:
+            raise ValueError(
+                f"Code execution is not supported for provider '{provider_name}'. "
+                "Supported providers: openai, anthropic, google."
+            )
+
+    @staticmethod
+    def _openai_definition(*, container_id: Optional[str] = None) -> "CodeInterpreter":
+        """Generate OpenAI code interpreter tool definition."""
+        # https://platform.openai.com/docs/guides/tools-code-interpreter
+        container = container_id or {"type": "auto"}
+        # dict[str, str] doesn't structurally satisfy CodeInterpreter's container union
+        return {"type": "code_interpreter", "container": container}  # type: ignore
+
+    @staticmethod
+    def _anthropic_definition() -> "BetaCodeExecutionTool20250522Param":
+        """Generate Anthropic/Claude code execution tool definition."""
+        # https://docs.claude.com/en/docs/agents-and-tools/tool-use/code-execution-tool
+        return {
+            "name": "code_execution",
+            "type": "code_execution_20250522",
+        }
+
+    @staticmethod
+    def _google_definition() -> "GoogleToolCodeExecution":
+        """Generate Google/Gemini code execution tool definition."""
+        # https://ai.google.dev/gemini-api/docs/code-execution
+        from google.genai.types import ToolCodeExecution as GoogleToolCodeExecution
+
+        return GoogleToolCodeExecution()
+
+
+def tool_code_execution() -> ToolCodeExecution:
+    """
+    Create a code execution tool for use with chat models.
+
+    This function creates a provider-agnostic code execution tool that can be
+    registered with any supported chat provider. The tool allows the model to
+    write and run code in a sandboxed environment and see the result -- e.g.
+    for math, data analysis, or verifying its own logic.
+
+    Supported providers: OpenAI, Claude (Anthropic), Google (Gemini)
+
+    Prerequisites
+    -------------
+    - **OpenAI**: Code execution is available by default with the Responses API.
+    - **Claude**: The code execution tool requires the beta header
+      `anthropic-beta: code-execution-2025-05-22`. Pass this via the `kwargs`
+      parameter's `default_headers` option (see examples below).
+    - **Google**: Code execution is available by default with Gemini.
+
+    Returns
+    -------
+    ToolCodeExecution
+        A code execution tool that can be registered with `chat.register_tool()`.
+
+    Examples
+    --------
+    ```python
+    from chatlas import ChatOpenAI, tool_code_execution
+
+    chat = ChatOpenAI()
+    chat.register_tool(tool_code_execution())
+    chat.chat("What's the 20th Fibonacci number?")
+    ```
+
+    ```python
+    from chatlas import ChatAnthropic, tool_code_execution
+
+    chat = ChatAnthropic(
+        kwargs={"default_headers": {"anthropic-beta": "code-execution-2025-05-22"}}
+    )
+    chat.register_tool(tool_code_execution())
+    chat.chat("What's the 20th Fibonacci number?")
+    ```
+
+    Note
+    ----
+    Only text output (stdout/stderr, or each provider's equivalent) is
+    surfaced as structured content. Files the code produces (e.g. plots,
+    CSVs) aren't downloaded or decoded -- their raw provider references are
+    still available via each content's `extra` attribute.
+
+    OpenAI reuses the same sandbox across turns in a conversation
+    automatically, so a variable defined in one turn is still available in
+    the next. Claude also reuses the same container across turns, but its
+    code execution tool does not persist Python interpreter state (e.g.
+    variables) between separate executions -- each execution starts fresh.
+    Google starts a fresh sandbox on every turn.
+    """
+    return ToolCodeExecution()
+
+
+def last_code_execution_container_id(turns: Sequence["Turn"]) -> Optional[str]:
+    """
+    Find the most recent code execution container/sandbox id in turn history.
+
+    Providers that support session reuse (OpenAI, Anthropic) key off this to
+    reuse the same sandbox across turns instead of starting a fresh one.
+    """
+    for turn in reversed(turns):
+        if not isinstance(turn, AssistantTurn):
+            continue
+        for content in reversed(turn.contents):
+            if (
+                isinstance(content, ContentToolResponseCodeExecution)
+                and content.container_id
+            ):
+                return content.container_id
+    return None
diff --git a/chatlas/types/__init__.py b/chatlas/types/__init__.py
index a6c5e580..408a0724 100644
--- a/chatlas/types/__init__.py
+++ b/chatlas/types/__init__.py
@@ -14,8 +14,10 @@
     ContentThinking,
     ContentThinkingDelta,
     ContentToolRequest,
+    ContentToolRequestCodeExecution,
     ContentToolRequestFetch,
     ContentToolRequestSearch,
+    ContentToolResponseCodeExecution,
     ContentToolResponseFetch,
     ContentToolResponseSearch,
     ContentToolResult,
@@ -46,6 +48,8 @@
     "ContentToolRequestSearch",
     "ContentToolResponseSearch",
     "FinishReason",
+    "ContentToolRequestCodeExecution",
+    "ContentToolResponseCodeExecution",
     "StructuredChatResult",
     "ChatResponse",
     "ChatResponseAsync",
diff --git a/docs/_quarto.yml b/docs/_quarto.yml
index 61b43e3a..d45e8cb0 100644
--- a/docs/_quarto.yml
+++ b/docs/_quarto.yml
@@ -184,10 +184,11 @@ quartodoc:
         - Tool
         - ToolRejectError
     - title: Built-in tools
-      desc: Provider-agnostic access to built-in web search and fetch capabilities.
+      desc: Provider-agnostic access to built-in web search, fetch, and code execution capabilities.
       contents:
         - tool_web_search
         - tool_web_fetch
+        - tool_code_execution
     - title: Parallel and batch chat
       desc: Submit multiple chats in parallel (fast) or one batch (cheap)
       contents:
diff --git a/docs/get-started/tools.qmd b/docs/get-started/tools.qmd
index a4e2f3ee..73114436 100644
--- a/docs/get-started/tools.qmd
+++ b/docs/get-started/tools.qmd
@@ -110,6 +110,31 @@ See the [MCP tools guide](../misc/mcp-tools.qmd) for more information.
 :::
 
 
+### Code execution
+
+Some providers can run code for you in a server-side sandbox -- useful for
+math, data analysis, or letting the model verify its own logic. Register it
+the same way as web search or fetch:
+
+```python
+from chatlas import ChatAnthropic, tool_code_execution
+
+chat = ChatAnthropic(
+    kwargs={"default_headers": {"anthropic-beta": "code-execution-2025-05-22"}}
+)
+chat.register_tool(tool_code_execution())
+chat.chat("What's the 20th Fibonacci number?")
+```
+
+Supported providers: OpenAI, Claude (Anthropic), Google (Gemini). Only text
+output (stdout/stderr) is surfaced -- files the code produces (e.g. plots)
+aren't downloaded automatically. OpenAI reuses the same sandbox across turns
+in a conversation, so state (like a variable) persists. Claude also reuses
+the same container across turns, but doesn't persist Python interpreter
+state between executions -- each execution starts fresh. Google starts a
+fresh sandbox every turn too.
+
+
 ### Tool errors
 
 When a tool function is called, it may fail for various reasons, such as network issues, invalid input, or unexpected exceptions.
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new file mode 100644
index 00000000..e2fe24cf
--- /dev/null
+++ b/tests/_vcr/test_provider_anthropic/test_anthropic_code_execution.yaml
@@ -0,0 +1,175 @@
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+      x-stainless-timeout:
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+      string: 'event: message_start
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+        event: content_block_start
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+
+        event: ping
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+
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+
+        event: content_block_delta
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+
+
+        event: content_block_delta
+
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+
+
+        event: content_block_delta
+
+        data: {"type":"content_block_delta","index":0,"delta":{"type":"input_json_delta","partial_json":"\"}"}     }
+
+
+        event: content_block_stop
+
+        data: {"type":"content_block_stop","index":0     }
+
+
+        event: content_block_start
+
+        data: {"type":"content_block_start","index":1,"content_block":{"type":"code_execution_tool_result","tool_use_id":"srvtoolu_018dAxW3UzAfH8W1pSrwuhbD","content":{"type":"code_execution_result","stdout":"6765","stderr":"","return_code":0,"content":[],"abort_reason":null}}        }
+
+
+        event: content_block_stop
+
+        data: {"type":"content_block_stop","index":1               }
+
+
+        event: content_block_start
+
+        data: {"type":"content_block_start","index":2,"content_block":{"type":"text","text":""}}
+
+
+        event: content_block_delta
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+        data: {"type":"content_block_delta","index":2,"delta":{"type":"text_delta","text":"The
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+
+
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+
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+
+
+        event: content_block_stop
+
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+
+
+        event: message_delta
+
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+
+
+        event: message_stop
+
+        data: {"type":"message_stop" }
+
+
+        '
+    headers:
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+      anthropic-ratelimit-input-tokens-remaining:
+      - '9999000'
+      anthropic-ratelimit-input-tokens-reset:
+      - '2026-07-21T21:59:28Z'
+      anthropic-ratelimit-output-tokens-limit:
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+      anthropic-ratelimit-output-tokens-remaining:
+      - '2000000'
+      anthropic-ratelimit-output-tokens-reset:
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+      anthropic-ratelimit-requests-limit:
+      - '20000'
+      anthropic-ratelimit-requests-remaining:
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+      anthropic-ratelimit-requests-reset:
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new file mode 100644
index 00000000..556c1e83
--- /dev/null
+++ b/tests/_vcr/test_provider_google/test_google_code_execution.yaml
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new file mode 100644
index 00000000..7bffe5df
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+        event: response.code_interpreter_call_code.delta
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+        event: response.code_interpreter_call_code.delta
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+        event: response.code_interpreter_call_code.delta
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+        data: {"type":"response.code_interpreter_call_code.delta","delta":"fib","item_id":"ci_050aaa8793a4eddc016a5fea2b88d8819480b746e8a50a7eec","obfuscation":"qIUXL9NOSdZnH","output_index":0,"sequence_number":41}
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+        event: response.code_interpreter_call_code.delta
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+        event: response.code_interpreter_call_code.delta
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+        data: {"type":"response.code_interpreter_call_code.delta","delta":" =","item_id":"ci_050aaa8793a4eddc016a5fea2b88d8819480b746e8a50a7eec","obfuscation":"5yGOcA2IH2xZNv","output_index":0,"sequence_number":44}
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+        event: response.code_interpreter_call_code.delta
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+        data: {"type":"response.code_interpreter_call_code.delta","delta":" fib","item_id":"ci_050aaa8793a4eddc016a5fea2b88d8819480b746e8a50a7eec","obfuscation":"uf7faDr2sXk7","output_index":0,"sequence_number":45}
+
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+        event: response.code_interpreter_call_code.delta
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+        event: response.code_interpreter_call_code.delta
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+        data: {"type":"response.code_interpreter_call_code.delta","delta":"20","item_id":"ci_050aaa8793a4eddc016a5fea2b88d8819480b746e8a50a7eec","obfuscation":"xQGiWd02oSaRxy","output_index":0,"sequence_number":47}
+
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+        event: response.code_interpreter_call_code.delta
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+
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+        event: response.code_interpreter_call_code.delta
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+
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+        event: response.code_interpreter_call_code.delta
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+        data: {"type":"response.code_interpreter_call_code.delta","delta":"_","item_id":"ci_050aaa8793a4eddc016a5fea2b88d8819480b746e8a50a7eec","obfuscation":"28gv1aaselBGhZv","output_index":0,"sequence_number":50}
+
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+        event: response.code_interpreter_call_code.delta
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+        data: {"type":"response.code_interpreter_call_code.delta","delta":"20","item_id":"ci_050aaa8793a4eddc016a5fea2b88d8819480b746e8a50a7eec","obfuscation":"WstJbkyJvcZ9q4","output_index":0,"sequence_number":51}
+
+
+        event: response.code_interpreter_call_code.done
+
+        data: {"type":"response.code_interpreter_call_code.done","code":"def fib(n):\r\n    a,
+        b = 0, 1\r\n    for _ in range(n):\r\n        a, b = b, a + b\r\n    return
+        a\r\n\r\nfib_20 = fib(20)\r\nfib_20","item_id":"ci_050aaa8793a4eddc016a5fea2b88d8819480b746e8a50a7eec","output_index":0,"sequence_number":52}
+
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+        event: response.code_interpreter_call.interpreting
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+        data: {"type":"response.code_interpreter_call.interpreting","item_id":"ci_050aaa8793a4eddc016a5fea2b88d8819480b746e8a50a7eec","output_index":0,"sequence_number":53}
+
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+        event: response.code_interpreter_call.completed
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+        data: {"type":"response.code_interpreter_call.completed","item_id":"ci_050aaa8793a4eddc016a5fea2b88d8819480b746e8a50a7eec","output_index":0,"sequence_number":54}
+
+
+        event: response.output_item.done
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+        data: {"type":"response.output_item.done","item":{"id":"ci_050aaa8793a4eddc016a5fea2b88d8819480b746e8a50a7eec","type":"code_interpreter_call","status":"completed","code":"def
+        fib(n):\r\n    a, b = 0, 1\r\n    for _ in range(n):\r\n        a, b = b,
+        a + b\r\n    return a\r\n\r\nfib_20 = fib(20)\r\nfib_20","container_id":"cntr_6a5fea2aff5c8193a1065b8c97a102160cefcd69266ffa1c","outputs":null},"output_index":0,"sequence_number":55}
+
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+        event: response.output_item.added
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+        data: {"type":"response.output_item.added","item":{"id":"msg_050aaa8793a4eddc016a5fea2d2ee88194b6955808c3796652","type":"message","status":"in_progress","content":[],"role":"assistant"},"output_index":1,"sequence_number":56}
+
+
+        event: response.content_part.added
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+        data: {"type":"response.content_part.added","content_index":0,"item_id":"msg_050aaa8793a4eddc016a5fea2d2ee88194b6955808c3796652","output_index":1,"part":{"type":"output_text","annotations":[],"logprobs":[],"text":""},"sequence_number":57}
+
+
+        event: response.output_text.delta
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+        data: {"type":"response.output_text.delta","content_index":0,"delta":"The","item_id":"msg_050aaa8793a4eddc016a5fea2d2ee88194b6955808c3796652","logprobs":[],"obfuscation":"B31oPGxZma4BA","output_index":1,"sequence_number":58}
+
+
+        event: response.output_text.delta
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+        data: {"type":"response.output_text.delta","content_index":0,"delta":" ","item_id":"msg_050aaa8793a4eddc016a5fea2d2ee88194b6955808c3796652","logprobs":[],"obfuscation":"Ej7MjFW0jzcysH5","output_index":1,"sequence_number":59}
+
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+        event: response.output_text.delta
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+        data: {"type":"response.output_text.delta","content_index":0,"delta":"20","item_id":"msg_050aaa8793a4eddc016a5fea2d2ee88194b6955808c3796652","logprobs":[],"obfuscation":"G8mLU9zXiPgkMP","output_index":1,"sequence_number":60}
+
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+        event: response.output_text.delta
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+        data: {"type":"response.output_text.delta","content_index":0,"delta":"th","item_id":"msg_050aaa8793a4eddc016a5fea2d2ee88194b6955808c3796652","logprobs":[],"obfuscation":"qMwCiACkYlAKmF","output_index":1,"sequence_number":61}
+
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+        event: response.output_text.delta
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+        data: {"type":"response.output_text.delta","content_index":0,"delta":" Fibonacci","item_id":"msg_050aaa8793a4eddc016a5fea2d2ee88194b6955808c3796652","logprobs":[],"obfuscation":"XJc5FN","output_index":1,"sequence_number":62}
+
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+        event: response.output_text.delta
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+        data: {"type":"response.output_text.delta","content_index":0,"delta":" number","item_id":"msg_050aaa8793a4eddc016a5fea2d2ee88194b6955808c3796652","logprobs":[],"obfuscation":"7pjY71ZXK","output_index":1,"sequence_number":63}
+
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+        event: response.output_text.delta
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+        data: {"type":"response.output_text.delta","content_index":0,"delta":" (","item_id":"msg_050aaa8793a4eddc016a5fea2d2ee88194b6955808c3796652","logprobs":[],"obfuscation":"VLCfOyJjxHu6D3","output_index":1,"sequence_number":64}
+
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+        event: response.output_text.delta
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+
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+        event: response.output_text.delta
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+        data: {"type":"response.output_text.delta","content_index":0,"delta":"-index","item_id":"msg_050aaa8793a4eddc016a5fea2d2ee88194b6955808c3796652","logprobs":[],"obfuscation":"HcAhqsIBL9","output_index":1,"sequence_number":66}
+
+
+        event: response.output_text.delta
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+        data: {"type":"response.output_text.delta","content_index":0,"delta":"ed","item_id":"msg_050aaa8793a4eddc016a5fea2d2ee88194b6955808c3796652","logprobs":[],"obfuscation":"vtE9neD9rdvAkO","output_index":1,"sequence_number":67}
+
+
+        event: response.output_text.delta
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+        data: {"type":"response.output_text.delta","content_index":0,"delta":")","item_id":"msg_050aaa8793a4eddc016a5fea2d2ee88194b6955808c3796652","logprobs":[],"obfuscation":"TCufQBYnYU5nyrz","output_index":1,"sequence_number":68}
+
+
+        event: response.output_text.delta
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+        data: {"type":"response.output_text.delta","content_index":0,"delta":" is","item_id":"msg_050aaa8793a4eddc016a5fea2d2ee88194b6955808c3796652","logprobs":[],"obfuscation":"5xBB7vmssQsym","output_index":1,"sequence_number":69}
+
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+        event: response.output_text.delta
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+        data: {"type":"response.output_text.delta","content_index":0,"delta":" ","item_id":"msg_050aaa8793a4eddc016a5fea2d2ee88194b6955808c3796652","logprobs":[],"obfuscation":"8GAXleuAAG4kbsn","output_index":1,"sequence_number":70}
+
+
+        event: response.output_text.delta
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+        data: {"type":"response.output_text.delta","content_index":0,"delta":"676","item_id":"msg_050aaa8793a4eddc016a5fea2d2ee88194b6955808c3796652","logprobs":[],"obfuscation":"FWjUWtduHTRUl","output_index":1,"sequence_number":71}
+
+
+        event: response.output_text.delta
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+        data: {"type":"response.output_text.delta","content_index":0,"delta":"5","item_id":"msg_050aaa8793a4eddc016a5fea2d2ee88194b6955808c3796652","logprobs":[],"obfuscation":"JpyTnUyXeFNref8","output_index":1,"sequence_number":72}
+
+
+        event: response.output_text.delta
+
+        data: {"type":"response.output_text.delta","content_index":0,"delta":".","item_id":"msg_050aaa8793a4eddc016a5fea2d2ee88194b6955808c3796652","logprobs":[],"obfuscation":"cwkKBPhQ8XMlsfb","output_index":1,"sequence_number":73}
+
+
+        event: response.output_text.done
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+        data: {"type":"response.output_text.done","content_index":0,"item_id":"msg_050aaa8793a4eddc016a5fea2d2ee88194b6955808c3796652","logprobs":[],"output_index":1,"sequence_number":74,"text":"The
+        20th Fibonacci number (0-indexed) is 6765."}
+
+
+        event: response.content_part.done
+
+        data: {"type":"response.content_part.done","content_index":0,"item_id":"msg_050aaa8793a4eddc016a5fea2d2ee88194b6955808c3796652","output_index":1,"part":{"type":"output_text","annotations":[],"logprobs":[],"text":"The
+        20th Fibonacci number (0-indexed) is 6765."},"sequence_number":75}
+
+
+        event: response.output_item.done
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+        data: {"type":"response.output_item.done","item":{"id":"msg_050aaa8793a4eddc016a5fea2d2ee88194b6955808c3796652","type":"message","status":"completed","content":[{"type":"output_text","annotations":[],"logprobs":[],"text":"The
+        20th Fibonacci number (0-indexed) is 6765."}],"role":"assistant"},"output_index":1,"sequence_number":76}
+
+
+        event: response.completed
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+
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+
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+
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+
+
+        event: response.output_text.delta
+
+        data: {"type":"response.output_text.delta","content_index":0,"delta":" ","item_id":"msg_0d4ae9317fe2724b016a5fea35163c8195b20b1772770f8d60","logprobs":[],"obfuscation":"9KGUXopLXojZHMc","output_index":1,"sequence_number":45}
+
+
+        event: response.output_text.delta
+
+        data: {"type":"response.output_text.delta","content_index":0,"delta":"84","item_id":"msg_0d4ae9317fe2724b016a5fea35163c8195b20b1772770f8d60","logprobs":[],"obfuscation":"wKQuk9twJDSJ2k","output_index":1,"sequence_number":46}
+
+
+        event: response.output_text.delta
+
+        data: {"type":"response.output_text.delta","content_index":0,"delta":".","item_id":"msg_0d4ae9317fe2724b016a5fea35163c8195b20b1772770f8d60","logprobs":[],"obfuscation":"Q8fhCgABVCYeOOm","output_index":1,"sequence_number":47}
+
+
+        event: response.output_text.done
+
+        data: {"type":"response.output_text.done","content_index":0,"item_id":"msg_0d4ae9317fe2724b016a5fea35163c8195b20b1772770f8d60","logprobs":[],"output_index":1,"sequence_number":48,"text":"The
+        result of `x * 2` using the previously defined `x` is 84."}
+
+
+        event: response.content_part.done
+
+        data: {"type":"response.content_part.done","content_index":0,"item_id":"msg_0d4ae9317fe2724b016a5fea35163c8195b20b1772770f8d60","output_index":1,"part":{"type":"output_text","annotations":[],"logprobs":[],"text":"The
+        result of `x * 2` using the previously defined `x` is 84."},"sequence_number":49}
+
+
+        event: response.output_item.done
+
+        data: {"type":"response.output_item.done","item":{"id":"msg_0d4ae9317fe2724b016a5fea35163c8195b20b1772770f8d60","type":"message","status":"completed","content":[{"type":"output_text","annotations":[],"logprobs":[],"text":"The
+        result of `x * 2` using the previously defined `x` is 84."}],"role":"assistant"},"output_index":1,"sequence_number":50}
+
+
+        event: response.completed
+
+        data: {"type":"response.completed","response":{"id":"resp_0d4ae9317fe2724b016a5fea31f17c8195b3036834d2f69bbc","object":"response","created_at":1784670770,"status":"completed","background":false,"completed_at":1784670773,"error":null,"frequency_penalty":0.0,"incomplete_details":null,"instructions":null,"max_output_tokens":null,"max_tool_calls":null,"model":"gpt-4.1-2025-04-14","moderation":null,"output":[{"id":"ci_0d4ae9317fe2724b016a5fea33959881958ac3a10224a0921d","type":"code_interpreter_call","status":"completed","code":"#
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+        result of `x * 2` using the previously defined `x` is 84."}],"role":"assistant"}],"parallel_tool_calls":true,"presence_penalty":0.0,"previous_response_id":null,"prompt_cache_key":null,"prompt_cache_retention":"in_memory","reasoning":{"context":null,"effort":null,"summary":null},"safety_identifier":null,"service_tier":"default","store":false,"temperature":1.0,"text":{"format":{"type":"text"},"verbosity":"medium"},"tool_choice":"auto","tool_usage":{"image_gen":{"input_tokens":0,"input_tokens_details":{"image_tokens":0,"text_tokens":0},"output_tokens":0,"output_tokens_details":{"image_tokens":0,"text_tokens":0},"total_tokens":0},"web_search":{"num_requests":0}},"tools":[{"type":"code_interpreter","container":"cntr_6a5fea2f61108193b410afd5e492da560f7799a7edfbd272"}],"top_logprobs":0,"top_p":1.0,"truncation":"disabled","usage":{"input_tokens":313,"input_tokens_details":{"cache_write_tokens":0,"cached_tokens":0},"output_tokens":46,"output_tokens_details":{"reasoning_tokens":0},"total_tokens":359},"user":null,"metadata":{}},"sequence_number":51}
+
+
+        '
+    headers:
+      access-control-expose-headers:
+      - X-Request-ID
+      - CF-Ray
+      - CF-Ray
+      alt-svc:
+      - h3=":443"; ma=86400
+      cf-cache-status:
+      - DYNAMIC
+      connection:
+      - keep-alive
+      content-type:
+      - text/event-stream; charset=utf-8
+      date:
+      - Tue, 21 Jul 2026 21:52:51 GMT
+      openai-processing-ms:
+      - '1363'
+      openai-version:
+      - '2020-10-01'
+      server:
+      - cloudflare
+      strict-transport-security:
+      - max-age=31536000; includeSubDomains; preload
+      transfer-encoding:
+      - chunked
+      x-content-type-options:
+      - nosniff
+      x-ratelimit-limit-requests:
+      - '10000'
+      x-ratelimit-limit-tokens:
+      - '30000000'
+      x-ratelimit-remaining-requests:
+      - '9999'
+      x-ratelimit-remaining-tokens:
+      - '29999702'
+      x-ratelimit-reset-requests:
+      - 6ms
+      x-ratelimit-reset-tokens:
+      - 0s
+    status:
+      code: 200
+      message: OK
+version: 1
diff --git a/tests/conftest.py b/tests/conftest.py
index 6bfcacaf..bdf72282 100644
--- a/tests/conftest.py
+++ b/tests/conftest.py
@@ -417,6 +417,39 @@ def assert_tool_web_search(chat_fun: ChatFun, tool, hint: str = "", stream: bool
     assert "May" in str(response)
 
 
+def assert_tool_code_execution(chat_fun: ChatFun, tool, stream: bool = True):
+    """Test code execution tool functionality."""
+    chat = chat_fun()
+    chat.register_tool(tool)
+
+    response = chat.chat(
+        "Use code execution to compute the 20th Fibonacci number "
+        "(0-indexed, so fib(0) = 0, fib(1) = 1). Just give me the number.",
+        stream=stream,
+    )
+    assert "6765" in str(response)
+
+
+def assert_tool_code_execution_persistence(
+    chat_fun: ChatFun, tool, stream: bool = True
+):
+    """Test that the sandbox persists a variable across turns."""
+    chat = chat_fun()
+    chat.register_tool(tool)
+
+    chat.chat(
+        "Use code execution to define a variable `x = 42`. "
+        "Don't print anything yet.",
+        stream=stream,
+    )
+    response = chat.chat(
+        "Now use code execution to print `x * 2`, reusing the same `x` "
+        "from before -- don't redefine it.",
+        stream=stream,
+    )
+    assert "84" in str(response)
+
+
 retry_api_call = retry(
     wait=wait_exponential(min=1, max=60),
     stop=stop_after_attempt(3),
diff --git a/tests/test_content_code_execution.py b/tests/test_content_code_execution.py
new file mode 100644
index 00000000..c5662bd2
--- /dev/null
+++ b/tests/test_content_code_execution.py
@@ -0,0 +1,69 @@
+from chatlas._content import (
+    ContentToolRequestCodeExecution,
+    ContentToolResponseCodeExecution,
+    ContentUnion,
+    create_content,
+)
+
+
+def test_content_tool_request_code_execution_defaults():
+    content = ContentToolRequestCodeExecution(code="print(1 + 1)")
+    assert content.content_type == "code_execution_request"
+    assert content.code == "print(1 + 1)"
+    assert content.language is None
+    assert content.extra is None
+
+
+def test_content_tool_request_code_execution_str():
+    content = ContentToolRequestCodeExecution(code="print(1 + 1)")
+    assert "print(1 + 1)" in str(content)
+
+
+def test_content_tool_response_code_execution_defaults():
+    content = ContentToolResponseCodeExecution(output="2")
+    assert content.content_type == "code_execution_result"
+    assert content.output == "2"
+    assert content.error is None
+    assert content.container_id is None
+    assert content.extra is None
+
+
+def test_content_tool_response_code_execution_str_with_output():
+    content = ContentToolResponseCodeExecution(output="2")
+    assert "2" in str(content)
+
+
+def test_content_tool_response_code_execution_str_with_error():
+    content = ContentToolResponseCodeExecution(error="NameError: x is not defined")
+    assert "NameError" in str(content)
+
+
+def test_create_content_round_trips_request():
+    content = ContentToolRequestCodeExecution(
+        code="print(1 + 1)", language="PYTHON", extra={"id": "abc"}
+    )
+    data = content.model_dump()
+    restored = create_content(data)
+    assert isinstance(restored, ContentToolRequestCodeExecution)
+    assert restored.code == "print(1 + 1)"
+    assert restored.language == "PYTHON"
+    assert restored.extra == {"id": "abc"}
+
+
+def test_create_content_round_trips_response():
+    content = ContentToolResponseCodeExecution(
+        output="2", container_id="cntr_123", extra={"id": "abc"}
+    )
+    data = content.model_dump()
+    restored = create_content(data)
+    assert isinstance(restored, ContentToolResponseCodeExecution)
+    assert restored.output == "2"
+    assert restored.container_id == "cntr_123"
+
+
+def test_content_union_includes_code_execution_types():
+    import typing
+
+    args = typing.get_args(ContentUnion)
+    assert ContentToolRequestCodeExecution in args
+    assert ContentToolResponseCodeExecution in args
diff --git a/tests/test_provider_anthropic.py b/tests/test_provider_anthropic.py
index 208e8508..a54a4ae8 100644
--- a/tests/test_provider_anthropic.py
+++ b/tests/test_provider_anthropic.py
@@ -7,6 +7,7 @@
     ChatAnthropic,
     UserTurn,
     content_image_file,
+    tool_code_execution,
     tool_web_fetch,
     tool_web_search,
 )
@@ -22,6 +23,7 @@
     assert_images_remote,
     assert_list_models,
     assert_pdf_local,
+    assert_tool_code_execution,
     assert_tool_web_fetch,
     assert_tool_web_search,
     assert_tools_async,
@@ -162,6 +164,26 @@ def test_anthropic_web_search_citations():
     assert has_citations, "Expected citations on text blocks from web search"
 
 
+@pytest.mark.vcr
+def test_anthropic_code_execution():
+    def chat_fun(**kwargs):
+        return ChatAnthropic(
+            kwargs={"default_headers": {"anthropic-beta": "code-execution-2025-05-22"}},
+            **kwargs,
+        )
+
+    assert_tool_code_execution(chat_fun, tool_code_execution())
+
+
+# N.B. no code execution *persistence* test for Anthropic: despite chatlas
+# reusing the same `container` across turns, Claude's code execution tool
+# does not persist Python REPL state (e.g. variables) across separate turns
+# -- each execution starts a fresh interpreter. This was verified live and
+# contradicts the tool's own SDK docstring ("REPL state persistence"), so
+# it's treated the same as Google's documented per-turn-fresh-sandbox
+# limitation rather than a bug in chatlas.
+
+
 @pytest.mark.vcr
 def test_data_extraction():
     assert_data_extraction(chat_func)
@@ -371,3 +393,184 @@ class Person(BaseModel):
     output_config = args["output_config"]
     assert output_config["effort"] == "high"
     assert output_config["format"]["type"] == "json_schema"
+
+
+def test_anthropic_code_execution_parses_request_and_response():
+    """server_tool_use(code_execution) + code_execution_tool_result parse correctly."""
+    from anthropic.types import Message
+    from chatlas._content import (
+        ContentToolRequestCodeExecution,
+        ContentToolResponseCodeExecution,
+    )
+    from chatlas._provider_anthropic import AnthropicProvider
+
+    chat = ChatAnthropic()
+    provider = chat.provider
+    assert isinstance(provider, AnthropicProvider)
+
+    message = Message.model_validate(
+        {
+            "id": "msg_1",
+            "type": "message",
+            "role": "assistant",
+            "model": "claude-opus-4-6",
+            "content": [
+                {
+                    "type": "server_tool_use",
+                    "id": "srvtoolu_1",
+                    "name": "code_execution",
+                    "input": {"code": "print(1 + 1)"},
+                },
+                {
+                    "type": "code_execution_tool_result",
+                    "tool_use_id": "srvtoolu_1",
+                    "content": {
+                        "type": "code_execution_result",
+                        "stdout": "2\n",
+                        "stderr": "",
+                        "return_code": 0,
+                        "content": [],
+                    },
+                },
+            ],
+            "stop_reason": "end_turn",
+            "usage": {"input_tokens": 10, "output_tokens": 5},
+            "container": {
+                "id": "cntr_xyz",
+                "expires_at": "2026-07-21T00:00:00Z",
+            },
+        }
+    )
+
+    turn = provider._as_turn(message, has_data_model=False)
+
+    assert len(turn.contents) == 2
+    request = turn.contents[0]
+    assert isinstance(request, ContentToolRequestCodeExecution)
+    assert request.code == "print(1 + 1)"
+
+    response = turn.contents[1]
+    assert isinstance(response, ContentToolResponseCodeExecution)
+    assert response.output == "2\n"
+    assert response.error is None
+    assert response.container_id == "cntr_xyz"
+
+
+def test_anthropic_code_execution_error_result():
+    """An error result maps to `error`, not `output`."""
+    from anthropic.types import Message
+    from chatlas._content import ContentToolResponseCodeExecution
+    from chatlas._provider_anthropic import AnthropicProvider
+
+    chat = ChatAnthropic()
+    provider = chat.provider
+    assert isinstance(provider, AnthropicProvider)
+
+    message = Message.model_validate(
+        {
+            "id": "msg_1",
+            "type": "message",
+            "role": "assistant",
+            "model": "claude-opus-4-6",
+            "content": [
+                {
+                    "type": "code_execution_tool_result",
+                    "tool_use_id": "srvtoolu_1",
+                    "content": {
+                        "type": "code_execution_tool_result_error",
+                        "error_code": "execution_time_exceeded",
+                    },
+                },
+            ],
+            "stop_reason": "end_turn",
+            "usage": {"input_tokens": 10, "output_tokens": 5},
+        }
+    )
+
+    turn = provider._as_turn(message, has_data_model=False)
+    response = turn.contents[0]
+    assert isinstance(response, ContentToolResponseCodeExecution)
+    assert response.output is None
+    assert response.error == "execution_time_exceeded"
+    assert response.container_id is None
+
+
+def test_anthropic_code_execution_tool_schema():
+    from chatlas._provider_anthropic import AnthropicProvider
+
+    schema = AnthropicProvider._anthropic_tool_schema(tool_code_execution())
+    assert schema["name"] == "code_execution"
+    assert schema["type"] == "code_execution_20250522"
+
+
+def test_anthropic_code_execution_container_reuse():
+    from chatlas._content import ContentToolResponseCodeExecution
+    from chatlas._provider_anthropic import AnthropicProvider
+    from chatlas._turn import AssistantTurn
+
+    chat = ChatAnthropic()
+    chat.register_tool(tool_code_execution())
+    provider = chat.provider
+    assert isinstance(provider, AnthropicProvider)
+
+    turns = [
+        AssistantTurn(
+            [ContentToolResponseCodeExecution(output="1", container_id="cntr_xyz")]
+        )
+    ]
+    kwargs = provider._chat_perform_args(
+        stream=False,
+        turns=turns,
+        tools=chat._tools,  # type: ignore[reportPrivateUsage]
+        data_model=None,
+        kwargs=None,
+    )
+    assert kwargs["container"] == "cntr_xyz"
+
+
+def test_anthropic_container_captured_from_streaming_message_delta():
+    """Anthropic only sends `container` on the message_delta event (not
+    message_start), so the streaming accumulator must copy it over -- otherwise
+    cross-turn container reuse silently never works when streaming (the
+    default `chat.chat()` mode)."""
+    from anthropic.types import Message, RawMessageDeltaEvent, RawMessageStartEvent
+    from chatlas._provider_anthropic import AnthropicProvider
+
+    chat = ChatAnthropic()
+    provider = chat.provider
+    assert isinstance(provider, AnthropicProvider)
+
+    start_message = Message.model_validate(
+        {
+            "id": "msg_1",
+            "type": "message",
+            "role": "assistant",
+            "model": "claude-opus-4-6",
+            "content": [],
+            "stop_reason": None,
+            "usage": {"input_tokens": 10, "output_tokens": 0},
+        }
+    )
+    start_chunk = RawMessageStartEvent.model_validate(
+        {"type": "message_start", "message": start_message.model_dump()}
+    )
+    completion = provider.stream_merge_chunks(None, start_chunk)
+    assert completion.container is None
+
+    delta_chunk = RawMessageDeltaEvent.model_validate(
+        {
+            "type": "message_delta",
+            "delta": {
+                "stop_reason": "end_turn",
+                "stop_sequence": None,
+                "container": {
+                    "id": "cntr_stream_xyz",
+                    "expires_at": "2026-07-21T00:00:00Z",
+                },
+            },
+            "usage": {"output_tokens": 5},
+        }
+    )
+    completion = provider.stream_merge_chunks(completion, delta_chunk)
+    assert completion.container is not None
+    assert completion.container.id == "cntr_stream_xyz"
diff --git a/tests/test_provider_google.py b/tests/test_provider_google.py
index 4d12fcab..95a562de 100644
--- a/tests/test_provider_google.py
+++ b/tests/test_provider_google.py
@@ -1,6 +1,12 @@
 import pytest
 import requests
-from chatlas import ChatGoogle, ChatVertex, tool_web_fetch, tool_web_search
+from chatlas import (
+    ChatGoogle,
+    ChatVertex,
+    tool_code_execution,
+    tool_web_fetch,
+    tool_web_search,
+)
 from chatlas._provider_google import (
     normalize_finish_reason as google_normalize_finish_reason,
 )
@@ -13,6 +19,7 @@
     assert_images_remote_error,
     assert_list_models,
     assert_pdf_local,
+    assert_tool_code_execution,
     assert_tool_web_fetch,
     assert_tool_web_search,
     assert_tools_parallel,
@@ -209,6 +216,12 @@ def test_google_web_search():
     assert_tool_web_search(chat_func, tool_web_search())
 
 
+@pytest.mark.vcr
+@retry_gemini_call
+def test_google_code_execution():
+    assert_tool_code_execution(chat_func, tool_code_execution())
+
+
 @pytest.mark.vcr
 @retry_gemini_call
 def test_images_inline():
@@ -602,3 +615,133 @@ def test_google_tool_config_not_set_when_tools_not_mixed():
     only_builtin = {"web_search": tool_web_search()}
     kwargs = provider._chat_perform_args(turns=[user_turn("hi")], tools=only_builtin)
     assert kwargs["config"].tool_config is None
+
+
+def test_google_code_execution_parses_request_and_response():
+    """executable_code + code_execution_result parts parse correctly."""
+    from chatlas._content import (
+        ContentToolRequestCodeExecution,
+        ContentToolResponseCodeExecution,
+    )
+    from chatlas._provider_google import GoogleProvider
+
+    provider = GoogleProvider(
+        model="gemini-2.5-flash-preview-04-17",
+        api_key="dummy",
+        kwargs=None,
+    )
+
+    message = {
+        "candidates": [
+            {
+                "content": {
+                    "parts": [
+                        {
+                            "executable_code": {
+                                "code": "print(1 + 1)",
+                                "language": "PYTHON",
+                            }
+                        },
+                        {
+                            "code_execution_result": {
+                                "outcome": "OUTCOME_OK",
+                                "output": "2\n",
+                            }
+                        },
+                    ]
+                },
+                "finish_reason": "STOP",
+            }
+        ],
+    }
+
+    turn = provider._as_turn(message, has_data_model=False)
+    assert len(turn.contents) == 2
+
+    request = turn.contents[0]
+    assert isinstance(request, ContentToolRequestCodeExecution)
+    assert request.code == "print(1 + 1)"
+    assert request.language == "PYTHON"
+
+    response = turn.contents[1]
+    assert isinstance(response, ContentToolResponseCodeExecution)
+    assert response.output == "2\n"
+    assert response.error is None
+
+
+def test_google_code_execution_failed_outcome_maps_to_error():
+    from chatlas._content import ContentToolResponseCodeExecution
+    from chatlas._provider_google import GoogleProvider
+
+    provider = GoogleProvider(
+        model="gemini-2.5-flash-preview-04-17",
+        api_key="dummy",
+        kwargs=None,
+    )
+
+    message = {
+        "candidates": [
+            {
+                "content": {
+                    "parts": [
+                        {
+                            "code_execution_result": {
+                                "outcome": "OUTCOME_FAILED",
+                                "output": "NameError: x is not defined",
+                            }
+                        },
+                    ]
+                },
+                "finish_reason": "STOP",
+            }
+        ],
+    }
+
+    turn = provider._as_turn(message, has_data_model=False)
+    response = turn.contents[0]
+    assert isinstance(response, ContentToolResponseCodeExecution)
+    assert response.output is None
+    assert response.error == "NameError: x is not defined"
+
+
+def test_google_code_execution_round_trip():
+    from chatlas._content import (
+        ContentToolRequestCodeExecution,
+        ContentToolResponseCodeExecution,
+    )
+    from chatlas._provider_google import GoogleProvider
+
+    provider = GoogleProvider(
+        model="gemini-2.5-flash-preview-04-17",
+        api_key="dummy",
+        kwargs=None,
+    )
+
+    request = ContentToolRequestCodeExecution(code="print(1 + 1)", language="PYTHON")
+    part = provider._as_part_type(request)
+    assert part.executable_code is not None
+    assert part.executable_code.code == "print(1 + 1)"
+
+    response = ContentToolResponseCodeExecution(output="2\n")
+    part = provider._as_part_type(response)
+    assert part.code_execution_result is not None
+    assert part.code_execution_result.output == "2\n"
+
+
+def test_google_code_execution_tool_definition_registered():
+    from chatlas._provider_google import GoogleProvider
+
+    provider = GoogleProvider(
+        model="gemini-2.5-flash-preview-04-17",
+        api_key="dummy",
+        kwargs=None,
+    )
+    kwargs = provider._chat_perform_args(
+        turns=[],
+        tools={"code_execution": tool_code_execution()},
+        data_model=None,
+        kwargs=None,
+    )
+    tools = kwargs["config"].tools
+    assert tools is not None
+    assert tools[0].code_execution is not None
diff --git a/tests/test_provider_openai.py b/tests/test_provider_openai.py
index 544986ba..41d8d3de 100644
--- a/tests/test_provider_openai.py
+++ b/tests/test_provider_openai.py
@@ -2,7 +2,7 @@
 
 import httpx
 import pytest
-from chatlas import ChatOpenAI, tool_web_search
+from chatlas import ChatOpenAI, tool_code_execution, tool_web_search
 from chatlas._provider_openai import (
     normalize_finish_reason as openai_normalize_finish_reason,
 )
@@ -14,6 +14,8 @@
     assert_images_remote,
     assert_list_models,
     assert_pdf_local,
+    assert_tool_code_execution,
+    assert_tool_code_execution_persistence,
     assert_tool_web_search,
     assert_tools_async,
     assert_tools_parallel,
@@ -130,6 +132,22 @@ def chat_fun(**kwargs):
     )
 
 
+@pytest.mark.vcr
+def test_openai_code_execution():
+    def chat_fun(**kwargs):
+        return ChatOpenAI(model="gpt-4.1", **kwargs)
+
+    assert_tool_code_execution(chat_fun, tool_code_execution())
+
+
+@pytest.mark.vcr
+def test_openai_code_execution_persistence():
+    def chat_fun(**kwargs):
+        return ChatOpenAI(model="gpt-4.1", **kwargs)
+
+    assert_tool_code_execution_persistence(chat_fun, tool_code_execution())
+
+
 @pytest.mark.vcr
 def test_openai_images():
     chat_fun = ChatOpenAI
@@ -336,3 +354,111 @@ def test_openai_custom_base_url_warning():
     with warnings.catch_warnings():
         warnings.simplefilter("error")
         check_base_url("https://api.openai.com/v1")
+
+
+def test_openai_code_execution_call_parses_request_and_response():
+    """A code_interpreter_call output splits into request + response content."""
+    from chatlas._content import (
+        ContentToolRequestCodeExecution,
+        ContentToolResponseCodeExecution,
+    )
+    from chatlas._provider_openai import OpenAIProvider
+
+    chat = ChatOpenAI()
+    provider = chat.provider
+    assert isinstance(provider, OpenAIProvider)
+
+    def make_response(outputs: list[dict]):
+        from openai.types.responses import Response
+
+        return Response.model_validate(
+            {
+                "id": "resp_1",
+                "created_at": 0,
+                "model": "gpt-4.1",
+                "object": "response",
+                "output": [
+                    {
+                        "id": "ci_1",
+                        "type": "code_interpreter_call",
+                        "status": "completed",
+                        "code": "print(1 + 1)",
+                        "container_id": "cntr_abc123",
+                        "outputs": outputs,
+                    }
+                ],
+                "parallel_tool_calls": True,
+                "tool_choice": "auto",
+                "tools": [],
+            }
+        )
+
+    resp = make_response([{"type": "logs", "logs": "2"}])
+    turn = provider._response_as_turn(resp, has_data_model=False)
+
+    assert len(turn.contents) == 2
+    request = turn.contents[0]
+    assert isinstance(request, ContentToolRequestCodeExecution)
+    assert request.code == "print(1 + 1)"
+
+    response = turn.contents[1]
+    assert isinstance(response, ContentToolResponseCodeExecution)
+    assert response.output == "2"
+    assert response.container_id == "cntr_abc123"
+
+
+def test_openai_code_execution_response_does_not_duplicate_on_round_trip():
+    """The response half shouldn't be resubmitted -- it's bundled into the request's extra."""
+    from chatlas._content import ContentToolResponseCodeExecution
+    from chatlas._provider_openai import as_input_param
+
+    content = ContentToolResponseCodeExecution(
+        output="2", extra={"type": "code_interpreter_call"}
+    )
+    assert as_input_param(content, "assistant") is None
+
+
+def test_openai_code_execution_tool_uses_auto_container_by_default():
+    from chatlas._provider_openai import OpenAIProvider
+
+    chat = ChatOpenAI()
+    chat.register_tool(tool_code_execution())
+    provider = chat.provider
+    assert isinstance(provider, OpenAIProvider)
+
+    kwargs = provider._chat_perform_args(
+        stream=False,
+        turns=[],
+        tools=chat._tools,  # type: ignore[reportPrivateUsage]
+        data_model=None,
+        kwargs=None,
+    )
+    tools = kwargs["tools"]
+    assert tools[0]["type"] == "code_interpreter"
+    assert tools[0]["container"] == {"type": "auto"}
+
+
+def test_openai_code_execution_tool_reuses_container_from_turn_history():
+    from chatlas._content import ContentToolResponseCodeExecution
+    from chatlas._provider_openai import OpenAIProvider
+    from chatlas._turn import AssistantTurn
+
+    chat = ChatOpenAI()
+    chat.register_tool(tool_code_execution())
+    provider = chat.provider
+    assert isinstance(provider, OpenAIProvider)
+
+    turns = [
+        AssistantTurn(
+            [ContentToolResponseCodeExecution(output="1", container_id="cntr_xyz")]
+        )
+    ]
+    kwargs = provider._chat_perform_args(
+        stream=False,
+        turns=turns,
+        tools=chat._tools,  # type: ignore[reportPrivateUsage]
+        data_model=None,
+        kwargs=None,
+    )
+    tools = kwargs["tools"]
+    assert tools[0]["container"] == "cntr_xyz"
diff --git a/tests/test_tools_builtin.py b/tests/test_tools_builtin.py
index ec20d314..6863237c 100644
--- a/tests/test_tools_builtin.py
+++ b/tests/test_tools_builtin.py
@@ -1,17 +1,22 @@
 """Tests for built-in web search and fetch tools."""
 
 import pytest
-
 from chatlas import (
     ChatAnthropic,
     ChatGoogle,
     ChatOpenAI,
+    tool_code_execution,
     tool_web_fetch,
     tool_web_search,
 )
 from chatlas._content import ToolAnnotations
 from chatlas._tools import ToolBuiltIn
-from chatlas._tools_builtin import ToolWebFetch, ToolWebSearch
+from chatlas._tools_builtin import (
+    ToolCodeExecution,
+    ToolWebFetch,
+    ToolWebSearch,
+    last_code_execution_container_id,
+)
 
 
 class TestToolBuiltInMetadata:
@@ -84,9 +89,7 @@ def test_cannot_use_both_domain_filters(self):
         with pytest.raises(
             ValueError, match="Cannot specify both allowed_domains and blocked_domains"
         ):
-            tool_web_search(
-                allowed_domains=["good.com"], blocked_domains=["bad.com"]
-            )
+            tool_web_search(allowed_domains=["good.com"], blocked_domains=["bad.com"])
 
     def test_with_user_location(self):
         """Test web search tool with user location."""
@@ -127,9 +130,7 @@ def test_cannot_use_both_domain_filters(self):
         with pytest.raises(
             ValueError, match="Cannot specify both allowed_domains and blocked_domains"
         ):
-            tool_web_fetch(
-                allowed_domains=["good.com"], blocked_domains=["bad.com"]
-            )
+            tool_web_fetch(allowed_domains=["good.com"], blocked_domains=["bad.com"])
 
 
 class TestToolWebSearchProviderDefinitions:
@@ -205,7 +206,9 @@ def test_unsupported_provider(self):
     def test_openai_warns_on_unsupported_params(self):
         """Test that OpenAI warns about unsupported parameters."""
         tool = tool_web_search(blocked_domains=["spam.com"], max_uses=5)
-        with pytest.warns(UserWarning, match="blocked_domains is not supported by OpenAI"):
+        with pytest.warns(
+            UserWarning, match="blocked_domains is not supported by OpenAI"
+        ):
             tool.get_definition("openai")
 
     def test_google_warns_on_unsupported_params(self):
@@ -287,7 +290,9 @@ def test_google_warns_on_unsupported_params(self):
         assert any("allowed_domains" in m for m in messages)
         assert any("max_uses" in m for m in messages)
 
-        with pytest.warns(UserWarning, match="blocked_domains is not supported by Google"):
+        with pytest.warns(
+            UserWarning, match="blocked_domains is not supported by Google"
+        ):
             tool2.get_definition("google")
 
     def test_anthropic_with_extra_params(self):
@@ -372,3 +377,116 @@ def add(x: int, y: int) -> int:
         assert len(tools) == 2
         tool_names = {t.name for t in tools}
         assert tool_names == {"web_search", "add"}
+
+
+class TestToolCodeExecutionConfiguration:
+    """Test ToolCodeExecution configuration and provider definitions."""
+
+    def test_has_description_and_annotations(self):
+        tool = tool_code_execution()
+        assert tool.description == "Execute code in a sandboxed environment."
+        assert tool.annotations is not None
+        assert tool.annotations["title"] == "Code execution"
+        assert tool.annotations["readOnlyHint"] is False
+        assert tool.annotations["openWorldHint"] is False
+
+    def test_basic_configuration(self):
+        tool = tool_code_execution()
+        assert isinstance(tool, ToolCodeExecution)
+        assert tool.name == "code_execution"
+
+    def test_openai_definition_defaults_to_auto_container(self):
+        tool = tool_code_execution()
+        definition = tool.get_definition("openai")
+        assert definition["type"] == "code_interpreter"
+        assert definition["container"] == {"type": "auto"}
+
+    def test_openai_definition_reuses_container_id(self):
+        tool = tool_code_execution()
+        definition = tool.get_definition("openai", container_id="cntr_abc123")
+        assert definition["container"] == "cntr_abc123"
+
+    def test_anthropic_definition(self):
+        tool = tool_code_execution()
+        definition = tool.get_definition("anthropic")
+        assert definition["name"] == "code_execution"
+        assert definition["type"] == "code_execution_20250522"
+
+    def test_google_definition(self):
+        from google.genai.types import ToolCodeExecution as GoogleToolCodeExecution
+
+        tool = tool_code_execution()
+        definition = tool.get_definition("google")
+        assert isinstance(definition, GoogleToolCodeExecution)
+
+    def test_unsupported_provider(self):
+        tool = tool_code_execution()
+        with pytest.raises(ValueError, match="Code execution is not supported"):
+            tool.get_definition("unsupported_provider")
+
+
+class TestLastCodeExecutionContainerId:
+    """Test the turn-history scan that powers cross-turn sandbox reuse."""
+
+    def test_returns_none_with_no_turns(self):
+        assert last_code_execution_container_id([]) is None
+
+    def test_returns_none_when_no_code_execution_response(self):
+        from chatlas._content import ContentText
+        from chatlas._turn import AssistantTurn
+
+        turns = [AssistantTurn([ContentText(text="hi")])]
+        assert last_code_execution_container_id(turns) is None
+
+    def test_finds_container_id_from_last_assistant_turn(self):
+        from chatlas._content import ContentToolResponseCodeExecution
+        from chatlas._turn import AssistantTurn, UserTurn
+
+        turns = [
+            UserTurn("define x = 1"),
+            AssistantTurn(
+                [ContentToolResponseCodeExecution(output="", container_id="cntr_1")]
+            ),
+            UserTurn("now print x"),
+            AssistantTurn(
+                [ContentToolResponseCodeExecution(output="1", container_id="cntr_2")]
+            ),
+        ]
+        assert last_code_execution_container_id(turns) == "cntr_2"
+
+    def test_ignores_response_without_container_id(self):
+        from chatlas._content import ContentToolResponseCodeExecution
+        from chatlas._turn import AssistantTurn
+
+        turns = [
+            AssistantTurn(
+                [ContentToolResponseCodeExecution(output="1", container_id="cntr_1")]
+            ),
+            AssistantTurn([ContentToolResponseCodeExecution(output="2")]),
+        ]
+        assert last_code_execution_container_id(turns) == "cntr_1"
+
+
+class TestChatRegistrationCodeExecution:
+    """Test registering the code execution tool with chat instances."""
+
+    def test_register_code_execution_openai(self):
+        chat = ChatOpenAI()
+        chat.register_tool(tool_code_execution())
+        tools = chat.get_tools()
+        assert len(tools) == 1
+        assert tools[0].name == "code_execution"
+
+    def test_register_code_execution_anthropic(self):
+        chat = ChatAnthropic()
+        chat.register_tool(tool_code_execution())
+        tools = chat.get_tools()
+        assert len(tools) == 1
+        assert tools[0].name == "code_execution"
+
+    def test_register_code_execution_google(self):
+        chat = ChatGoogle()
+        chat.register_tool(tool_code_execution())
+        tools = chat.get_tools()
+        assert len(tools) == 1
+        assert tools[0].name == "code_execution"