mirror of
https://github.com/microsoft/agent-framework.git
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Eduard van Valkenburg
a2856d3b92
* restructure: Python samples into progressive 01-05 layout - 01-get-started/: 6 numbered steps (hello agent → hosting) - 02-agents/: all agent concept samples (tools, middleware, providers, etc.) - 03-workflows/: ALL existing workflow samples preserved as-is - 04-hosting/: azure-functions, durabletask, a2a - 05-end-to-end/: demos, evaluation, hosted agents - Old files moved to _to_delete/ for review - Added AGENTS.md with structure documentation - autogen-migration/ and semantic-kernel-migration/ preserved at root * fix: switch to AzureOpenAI Foundry, fix CI failures - Switch all 01-get-started samples to AzureOpenAIResponsesClient with Azure AI Foundry project endpoint (AZURE_AI_PROJECT_ENDPOINT + AZURE_OPENAI_RESPONSES_DEPLOYMENT_NAME + AzureCliCredential) - Add _to_delete/ and 05-end-to-end/ to pyrightconfig.samples.json excludes - Fix test paths in packages/ that referenced old getting_started/ dirs: durabletask conftest + streaming test, azurefunctions conftest, devui conftest + capture_messages + openai_sdk_integration - Fix workflow_as_agent_human_in_the_loop.py import (sibling import) - Update hosting READMEs and tool comment paths - Replace root README.md with new structure overview - Update AGENTS.md to document Azure OpenAI Foundry as default provider * cleanup: remove _to_delete folder, copy resource files to active dirs All files in _to_delete/ were either: - Exact duplicates of files in the new structure (240 files) - Same file with only comment path updates (100 files) - One import-fix diff (workflow_as_agent_human_in_the_loop.py) - One superseded minimal_sample.py Resource files (sample.pdf, countries.json, employees.pdf, weather.json) copied to 02-agents/sample_assets/ and 02-agents/resources/ since active samples reference them. * fix: address PR review comments, centralize resources, remove root duplicates - Fix type annotation in 04_memory.py (string union -> proper types) - Fix old sample paths in observability files - Fix grammar/spelling in observability samples - Move sample_assets/ and resources/ to shared/ folder - Remove 8 duplicate observability files from 02-agents root - Update resource path references in multimodal_input and provider samples * fix: update broken links from old getting_started paths to new structure - Update relative paths in READMEs: getting_started/ → 01-get-started/, 02-agents/, 03-workflows/, 04-hosting/, 05-end-to-end/ - Fix absolute GitHub URLs in package READMEs - Fix broken link in ollama package README * fix: convert absolute GitHub URLs to relative paths for link checker Absolute URLs to python/samples/ on main branch 404 until PR merges. Converted to relative paths that linkspector can verify locally. * fix: update link for handoff sample moved to orchestrations/ * fix: update chatkit-integration README path from demos/ to 05-end-to-end/ * fix: update broken links in orchestrations README to match flat directory structure
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 OpenAIResponsesClient
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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_RESPONSES_MODEL_ID: 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 = OpenAIResponsesClient()
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github_mcp_tool = client.get_mcp_tool(
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server_label="GitHub",
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server_url="https://api.githubcopilot.com/mcp/",
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headers=auth_headers,
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require_approval="never",
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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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