feat: add support for funnel reports

README.md

@@ -36,6 +36,7 @@ to provide several
 ### Run core reports 📙
 
 - `run_report`: Runs a Google Analytics report using the Data API.
+- `run_funnel_report`: Runs a Google Analytics funnel report using the Data API.
 - `get_custom_dimensions_and_metrics`: Retrieves the custom dimensions and
   metrics for a specific property.
 

analytics_mcp/server.py

@@ -25,6 +25,7 @@
 from analytics_mcp.tools.admin import info  # noqa: F401
 from analytics_mcp.tools.reporting import realtime  # noqa: F401
 from analytics_mcp.tools.reporting import core  # noqa: F401
+from analytics_mcp.tools.reporting import funnel  # noqa: F401
 
 
 def run_server() -> None:

analytics_mcp/tools/reporting/funnel.py

@@ -0,0 +1,177 @@
+from typing import Any, Dict, List
+
+from analytics_mcp.coordinator import mcp
+from analytics_mcp.tools.reporting.metadata import (
+    get_date_ranges_hints,
+    get_funnel_steps_hints,
+)
+from analytics_mcp.tools.utils import (
+    construct_property_rn,
+    create_data_api_alpha_client,
+    proto_to_dict,
+)
+from google.analytics import data_v1alpha
+
+
+def _run_funnel_report_description() -> str:
+    """Returns the description for the `run_funnel_report` tool."""
+    return f"""
+        {run_funnel_report.__doc__}
+
+        ## Hints for arguments
+
+        Here are some hints that outline the expected format and requirements
+        for arguments.
+
+        ### Hints for `funnel_breakdown`
+
+        The `funnel_breakdown` parameter allows you to segment funnel results by a dimension:
+        ```json
+        {{
+            "breakdown_dimension": "deviceCategory"
+        }}
+        ```
+        Common breakdown dimensions include:
+        - `deviceCategory` - Desktop, Mobile, Tablet
+        - `country` - User's country
+        - `operatingSystem` - User's operating system
+        - `browser` - User's browser
+
+        ### Hints for `funnel_next_action`
+
+        The `funnel_next_action` parameter analyzes what users do after completing or dropping off from the funnel:
+        ```json
+        {{
+            "next_action_dimension": "eventName",
+            "limit": 5
+        }}
+        ```
+        Common next action dimensions include:
+        - `eventName` - Next events users trigger
+        - `pagePath` - Next pages users visit
+
+        ### Hints for `date_ranges`:
+        {get_date_ranges_hints()}
+
+        ### Hints for `funnel_steps`
+        {get_funnel_steps_hints()}
+
+        """
+
+
+async def run_funnel_report(
+    property_id: int | str,
+    funnel_steps: List[Dict[str, Any]],
+    date_ranges: List[Dict[str, str]] = None,
+    funnel_breakdown: Dict[str, str] = None,
+    funnel_next_action: Dict[str, str] = None,
+    segments: List[Dict[str, Any]] = None,
+    return_property_quota: bool = False,
+) -> Dict[str, Any]:
+    """Run a Google Analytics Data API funnel report.
+
+    See the funnel report guide at
+    https://developers.google.com/analytics/devguides/reporting/data/v1/funnels
+    for details and examples.
+
+    Args:
+        property_id: The Google Analytics property ID. Accepted formats are:
+          - A number
+          - A string consisting of 'properties/' followed by a number
+        funnel_steps: A list of funnel steps. Each step should be a dictionary
+          containing:
+          - 'name': (str) Display name for the step
+          - 'filter_expression': (Dict) Complete filter expression for the step
+          OR for simple event-based steps:
+          - 'name': (str) Display name for the step
+          - 'event': (str) Event name to filter on
+        date_ranges: A list of date ranges
+          (https://developers.google.com/analytics/devguides/reporting/data/v1/rest/v1beta/DateRange)
+          to include in the report.
+        funnel_breakdown: Optional breakdown dimension to segment the funnel.
+          This creates separate funnel results for each value of the dimension.
+          Example: {"breakdown_dimension": "deviceCategory"}
+        funnel_next_action: Optional next action analysis configuration.
+          This analyzes what users do after completing or dropping off from the funnel.
+          Example: {"next_action_dimension": "eventName", "limit": 5}
+        segments: Optional list of segments to apply to the funnel.
+        return_property_quota: Whether to return current property quota information.
+
+    Returns:
+        Dict containing the funnel report response with funnel results including:
+        - funnel_table: Table showing progression through funnel steps
+        - funnel_visualization: Data for visualizing the funnel
+        - property_quota: (if requested) Current quota usage information
+
+    Raises:
+        ValueError: If funnel_steps is empty or contains invalid configurations
+        Exception: If the API request fails
+
+
+    """
+
+    steps = []
+    for i, step in enumerate(funnel_steps):
+        if not isinstance(step, dict):
+            raise ValueError(f"Step {i+1} must be a dictionary")
+
+        step_name = step.get("name", f"Step {i+1}")
+
+        if "filter_expression" in step:
+            filter_expr = data_v1alpha.FunnelFilterExpression(
+                step["filter_expression"]
+            )
+        elif "event" in step:
+            filter_expr = data_v1alpha.FunnelFilterExpression(
+                funnel_event_filter=data_v1alpha.FunnelEventFilter(
+                    event_name=step["event"]
+                )
+            )
+        else:
+            raise ValueError(
+                f"Step {i+1} must contain either 'filter_expression' or 'event' key"
+            )
+
+        funnel_step = data_v1alpha.FunnelStep(
+            name=step_name, filter_expression=filter_expr
+        )
+        steps.append(funnel_step)
+
+    request = data_v1alpha.RunFunnelReportRequest(
+        property=construct_property_rn(property_id),
+        funnel=data_v1alpha.Funnel(steps=steps),
+        date_ranges=[data_v1alpha.DateRange(dr) for dr in date_ranges],
+        return_property_quota=return_property_quota,
+    )
+
+    if funnel_breakdown and "breakdown_dimension" in funnel_breakdown:
+        request.funnel_breakdown = data_v1alpha.FunnelBreakdown(
+            breakdown_dimension=data_v1alpha.Dimension(
+                name=funnel_breakdown["breakdown_dimension"]
+            )
+        )
+
+    if funnel_next_action and "next_action_dimension" in funnel_next_action:
+        next_action_config = data_v1alpha.FunnelNextAction(
+            next_action_dimension=data_v1alpha.Dimension(
+                name=funnel_next_action["next_action_dimension"]
+            )
+        )
+        if "limit" in funnel_next_action:
+            next_action_config.limit = funnel_next_action["limit"]
+        request.funnel_next_action = next_action_config
+
+    if segments:
+        request.segments = [
+            data_v1alpha.Segment(segment) for segment in segments
+        ]
+
+    response = await create_data_api_alpha_client().run_funnel_report(request)
+    return proto_to_dict(response)
+
+
+mcp.add_tool(
+    run_funnel_report,
+    title="Run a Google Analytics Data API funnel report using the Data API",
+    description=_run_funnel_report_description(),
+)

analytics_mcp/tools/reporting/metadata.py

@@ -56,6 +56,173 @@ def get_date_ranges_hints():
     """
 
 
+def get_funnel_steps_hints():
+    """Returns hints and examples for funnel steps configuration."""
+    from google.analytics import data_v1alpha
+
+    step_first_open = data_v1alpha.FunnelStep(
+        name="First open/visit",
+        filter_expression=data_v1alpha.FunnelFilterExpression(
+            or_group=data_v1alpha.FunnelFilterExpressionList(
+                expressions=[
+                    data_v1alpha.FunnelFilterExpression(
+                        funnel_event_filter=data_v1alpha.FunnelEventFilter(
+                            event_name="first_open"
+                        )
+                    ),
+                    data_v1alpha.FunnelFilterExpression(
+                        funnel_event_filter=data_v1alpha.FunnelEventFilter(
+                            event_name="first_visit"
+                        )
+                    ),
+                ]
+            )
+        ),
+    )
+
+    step_organic_visitors = data_v1alpha.FunnelStep(
+        name="Organic visitors",
+        filter_expression=data_v1alpha.FunnelFilterExpression(
+            funnel_field_filter=data_v1alpha.FunnelFieldFilter(
+                field_name="firstUserMedium",
+                string_filter=data_v1alpha.StringFilter(
+                    match_type=data_v1alpha.StringFilter.MatchType.CONTAINS,
+                    case_sensitive=False,
+                    value="organic",
+                ),
+            )
+        ),
+    )
+
+    step_session_start = data_v1alpha.FunnelStep(
+        name="Session start",
+        filter_expression=data_v1alpha.FunnelFilterExpression(
+            funnel_event_filter=data_v1alpha.FunnelEventFilter(
+                event_name="session_start"
+            )
+        ),
+    )
+
+    step_page_view = data_v1alpha.FunnelStep(
+        name="Screen/Page view",
+        filter_expression=data_v1alpha.FunnelFilterExpression(
+            or_group=data_v1alpha.FunnelFilterExpressionList(
+                expressions=[
+                    data_v1alpha.FunnelFilterExpression(
+                        funnel_event_filter=data_v1alpha.FunnelEventFilter(
+                            event_name="screen_view"
+                        )
+                    ),
+                    data_v1alpha.FunnelFilterExpression(
+                        funnel_event_filter=data_v1alpha.FunnelEventFilter(
+                            event_name="page_view"
+                        )
+                    ),
+                ]
+            )
+        ),
+    )
+
+    step_purchase = data_v1alpha.FunnelStep(
+        name="Purchase",
+        filter_expression=data_v1alpha.FunnelFilterExpression(
+            or_group=data_v1alpha.FunnelFilterExpressionList(
+                expressions=[
+                    data_v1alpha.FunnelFilterExpression(
+                        funnel_event_filter=data_v1alpha.FunnelEventFilter(
+                            event_name="purchase"
+                        )
+                    ),
+                    data_v1alpha.FunnelFilterExpression(
+                        funnel_event_filter=data_v1alpha.FunnelEventFilter(
+                            event_name="in_app_purchase"
+                        )
+                    ),
+                ]
+            )
+        ),
+    )
+
+    step_add_to_cart_value = data_v1alpha.FunnelStep(
+        name="Add to cart (value > 50)",
+        filter_expression=data_v1alpha.FunnelFilterExpression(
+            funnel_event_filter=data_v1alpha.FunnelEventFilter(
+                event_name="add_to_cart",
+                funnel_parameter_filter_expression=data_v1alpha.FunnelParameterFilterExpression(
+                    funnel_parameter_filter=data_v1alpha.FunnelParameterFilter(
+                        event_parameter_name="value",
+                        numeric_filter=data_v1alpha.NumericFilter(
+                            operation=data_v1alpha.NumericFilter.Operation.GREATER_THAN,
+                            value=data_v1alpha.NumericValue(double_value=50.0),
+                        ),
+                    )
+                ),
+            )
+        ),
+    )
+
+    step_home_page_view = data_v1alpha.FunnelStep(
+        name="Home page view",
+        filter_expression=data_v1alpha.FunnelFilterExpression(
+            and_group=data_v1alpha.FunnelFilterExpressionList(
+                expressions=[
+                    data_v1alpha.FunnelFilterExpression(
+                        funnel_event_filter=data_v1alpha.FunnelEventFilter(
+                            event_name="page_view"
+                        )
+                    ),
+                    data_v1alpha.FunnelFilterExpression(
+                        funnel_field_filter=data_v1alpha.FunnelFieldFilter(
+                            field_name="pagePath",
+                            string_filter=data_v1alpha.StringFilter(
+                                match_type=data_v1alpha.StringFilter.MatchType.EXACT,
+                                value="/",
+                            ),
+                        )
+                    ),
+                ]
+            )
+        ),
+    )
+
+    return f"""Example funnel_steps configurations:
+
+    1. Simple event-based step (first open/visit):
+        {proto_to_json(step_first_open)}
+
+    2. Field filter for organic traffic:
+        {proto_to_json(step_organic_visitors)}
+
+    3. Simple event filter:
+        {proto_to_json(step_session_start)}
+
+    4. Multiple events with OR condition:
+        {proto_to_json(step_page_view)}
+
+    5. Purchase events (multiple event types):
+        {proto_to_json(step_purchase)}
+
+    6. Event with parameter filter (value > 50):
+        {proto_to_json(step_add_to_cart_value)}
+
+    7. Complex AND condition (page view + specific path):
+        {proto_to_json(step_home_page_view)}
+
+
+    ## Complete Funnel Example
+
+    A typical e-commerce funnel with 5 steps:
+    [
+        {proto_to_json(step_first_open)},
+        {proto_to_json(step_organic_visitors)},
+        {proto_to_json(step_session_start)},
+        {proto_to_json(step_page_view)},
+        {proto_to_json(step_purchase)}
+    ]
+
+    """
+
+
 # Common notes to consider when applying dimension and metric filters.
 _FILTER_NOTES = """
   Notes:

analytics_mcp/tools/utils.py

@@ -16,7 +16,7 @@
 
 from typing import Any, Dict
 
-from google.analytics import admin_v1beta, data_v1beta
+from google.analytics import admin_v1beta, data_v1beta, data_v1alpha
 from google.api_core.gapic_v1.client_info import ClientInfo
 from importlib import metadata
 import google.auth
@@ -71,6 +71,18 @@ def create_data_api_client() -> data_v1beta.BetaAnalyticsDataAsyncClient:
     )
 
 
+def create_data_api_alpha_client() -> (
+    data_v1alpha.AlphaAnalyticsDataAsyncClient
+):
+    """Returns a properly configured Google Analytics Data API (Alpha) async client.
+
+    Uses Application Default Credentials with read-only scope.
+    """
+    return data_v1alpha.AlphaAnalyticsDataAsyncClient(
+        client_info=_CLIENT_INFO, credentials=_create_credentials()
+    )
+
+
 def construct_property_rn(property_value: int | str) -> str:
     """Returns a property resource name in the format required by APIs."""
     property_num = None