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38 lines
2.6 KiB
Markdown
38 lines
2.6 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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| **Long-Running Task** | [`mcp_long_running_task.py`](mcp_long_running_task.py) | Demonstrates transparent SEP-2663 long-running task handling for MCP tools that advertise `taskSupport=required`. Self-spawns a stdio MCP child server |
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| **Progressive Disclosure** | [`mcp_progressive_disclosure.py`](mcp_progressive_disclosure.py) | Demonstrates `use_progressive_disclosure`, `always_load`, `allowed_tools`, and prefixed `list_mcp_tools` / `load_tool` / `unload_tool` names. `load_tool` and `unload_tool` can accept one tool name or multiple names. Self-spawns a stdio MCP child server |
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| **Sampling Approval** | [`mcp_sampling_approval.py`](mcp_sampling_approval.py) | Demonstrates gating server-initiated `sampling/createMessage` requests with a `sampling_approval_callback`, plus the `sampling_max_tokens` and `sampling_max_requests` guardrails. MCP sampling is denied by default |
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## Prerequisites
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Most samples in this folder use OpenAI:
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- `OPENAI_API_KEY` environment variable
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- `OPENAI_CHAT_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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`mcp_progressive_disclosure.py` self-spawns its demo MCP stdio server; no separate MCP server setup is required.
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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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For `mcp_long_running_task.py` (uses Azure OpenAI via Entra-ID):
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- Run `az login` once
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- `AZURE_OPENAI_ENDPOINT` - your Azure OpenAI resource endpoint, e.g. `https://<resource>.openai.azure.com/`
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- `AZURE_OPENAI_CHAT_MODEL` (or `AZURE_OPENAI_MODEL`) - the deployment name (e.g. `gpt-4o-mini`)
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