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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>
82 lines
2.9 KiB
Python
82 lines
2.9 KiB
Python
# Copyright (c) Microsoft. All rights reserved.
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import asyncio
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import os
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from agent_framework import Agent
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from agent_framework.openai import OpenAIChatClient
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from dotenv import load_dotenv
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"""
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MCP GitHub Integration with Personal Access Token (PAT)
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This example demonstrates how to connect to GitHub's remote MCP server using a Personal Access
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Token (PAT) for authentication. The agent can use GitHub operations like searching repositories,
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reading files, creating issues, and more depending on how you scope your token.
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Prerequisites:
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1. A GitHub Personal Access Token with appropriate scopes
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- Create one at: https://github.com/settings/tokens
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- For read-only operations, you can use more restrictive scopes
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2. Environment variables:
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- GITHUB_PAT: Your GitHub Personal Access Token (required)
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- OPENAI_API_KEY: Your OpenAI API key (required)
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- OPENAI_MODEL: Your OpenAI model ID (required)
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"""
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async def github_mcp_example() -> None:
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"""Example of using GitHub MCP server with PAT authentication."""
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# 1. Load environment variables from .env file if present
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load_dotenv()
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# 2. Get configuration from environment
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github_pat = os.getenv("GITHUB_PAT")
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if not github_pat:
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raise ValueError(
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"GITHUB_PAT environment variable must be set. Create a token at https://github.com/settings/tokens"
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)
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# 3. Create authentication headers with GitHub PAT
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auth_headers = {
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"Authorization": f"Bearer {github_pat}",
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}
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# 4. Create agent with the GitHub MCP tool using instance method
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# The MCP tool manages the connection to the MCP server and makes its tools available
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# Set approval_mode="never_require" to allow the MCP tool to execute without approval
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client = OpenAIChatClient()
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github_mcp_tool = client.get_mcp_tool(
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name="GitHub",
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url="https://api.githubcopilot.com/mcp/",
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headers=auth_headers,
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approval_mode="never_require",
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)
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# 5. Create agent with the GitHub MCP tool
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async with Agent(
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client=client,
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name="GitHubAgent",
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instructions=(
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"You are a helpful assistant that can help users interact with GitHub. "
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"You can search for repositories, read file contents, check issues, and more. "
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"Always be clear about what operations you're performing."
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),
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tools=github_mcp_tool,
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) as agent:
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# Example 1: Get authenticated user information
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query1 = "What is my GitHub username and tell me about my account?"
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print(f"\nUser: {query1}")
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result1 = await agent.run(query1)
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print(f"Agent: {result1.text}")
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# Example 2: List my repositories
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query2 = "List all the repositories I own on GitHub"
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print(f"\nUser: {query2}")
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result2 = await agent.run(query2)
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print(f"Agent: {result2.text}")
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if __name__ == "__main__":
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asyncio.run(github_mcp_example())
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