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Eduard van Valkenburg
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* Python: Add header_provider to MCPStreamableHTTPTool (#4808) Add a header_provider callback parameter to MCPStreamableHTTPTool that enables injecting dynamic per-request HTTP headers from runtime kwargs (originating from FunctionInvocationContext.kwargs set in agent middleware). The implementation uses contextvars and httpx event hooks to ensure headers are task-local and safe for concurrent tool calls: - header_provider receives the runtime kwargs dict and returns headers - call_tool sets a ContextVar before delegating to MCPTool.call_tool - An httpx request event hook reads from the ContextVar and injects headers Example usage: mcp_tool = MCPStreamableHTTPTool( name="web-api", url="https://api.example.com/mcp", header_provider=lambda kwargs: { "X-Auth-Token": kwargs.get("auth_token", ""), }, ) Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Address review feedback for #4808: Python: [Bug]: Unable to pass AgentContext to MCPStreamableHTTPTool * Add test for header_provider via FunctionTool.invoke with FunctionInvocationContext Addresses PR review comment: exercises the full pipeline from FunctionInvocationContext.kwargs through FunctionTool.invoke to MCPStreamableHTTPTool.call_tool and header_provider, rather than testing call_tool in isolation. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Address review feedback for #4808: review comment fixes * Fix streamable MCP transport defaults Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Fix Azure AI test client mocks Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Fix MCP runtime kwarg regressions Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Stabilize MCP tool runtime kwargs Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Use context kwargs in MCP wrappers Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * updated mcp samples * fix link --------- Co-authored-by: Copilot <copilot@github.com> Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
26 lines
1.3 KiB
Markdown
26 lines
1.3 KiB
Markdown
# MCP (Model Context Protocol) Examples
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This folder contains examples demonstrating how to work with MCP using Agent Framework.
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## What is MCP?
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The Model Context Protocol (MCP) is an open standard for connecting AI agents to data sources and tools. It enables secure, controlled access to local and remote resources through a standardized protocol.
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## Examples
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| Sample | File | Description |
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| **Agent as MCP Server** | [`agent_as_mcp_server.py`](agent_as_mcp_server.py) | Shows how to expose an Agent Framework agent as an MCP server that other AI applications can connect to |
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| **API Key Authentication** | [`mcp_api_key_auth.py`](mcp_api_key_auth.py) | Demonstrates API key authentication with MCP servers using `header_provider`, runtime invocation kwargs, and a command-line API key argument |
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| **GitHub Integration with PAT** | [`mcp_github_pat.py`](mcp_github_pat.py) | Demonstrates connecting to GitHub's MCP server using Personal Access Token (PAT) authentication |
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## Prerequisites
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- `OPENAI_API_KEY` environment variable
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- `OPENAI_RESPONSES_MODEL` environment variable
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Run `mcp_api_key_auth.py` with the MCP API key as the first command-line argument.
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For `mcp_github_pat.py`:
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- `GITHUB_PAT` - Your GitHub Personal Access Token (create at https://github.com/settings/tokens)
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