Skip to content

README.md

Latest commit

 

History

History
39 lines (26 loc) · 1.62 KB

README.md

File metadata and controls

39 lines (26 loc) · 1.62 KB

Hosted MCP Examples

Integration with hosted MCP (Model Context Protocol) servers using OpenAI agents in Temporal workflows.

Adapted from OpenAI Agents SDK hosted_mcp examples

Before running these examples, be sure to review the prerequisites and background on the integration.

Running the Examples

First, start the worker (supports all MCP workflows):

uv run openai_agents/hosted_mcp/run_worker.py

Then run individual examples in separate terminals:

Simple MCP Connection

Connect to a hosted MCP server without approval requirements (trusted servers):

uv run openai_agents/hosted_mcp/run_simple_mcp_workflow.py

MCP with Approval Callbacks

Connect to a hosted MCP server with approval workflow for tool execution:

uv run openai_agents/hosted_mcp/run_approval_mcp_workflow.py

MCP Server Configuration

Both examples default to using the GitMCP server (https://gitmcp.io/openai/codex) which provides repository analysis capabilities. The workflows can be easily modified to use different MCP servers by changing the server_url parameter.

Approval Workflow Notes

The approval example demonstrates the callback structure for tool approvals in a Temporal context. In this implementation:

  • The approval callback automatically approves requests for demonstration purposes
  • In production environments, approvals would typically be handled by communicating with a human user. Because the approval executes in the Temporal workflow, you can use signals or updates to communicate approval status.