Mcp_proxy_pydantic_agent
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Example for exposing MCP servers to Pydantic Agents
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- Author
- p2c2e
- GitHub stars
- 18
- Downloads
- 188
- Categories
- AI
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- Integrates MCP servers with Pydantic.AI agents
- Uses two different LLMs (gpt‑4o and sonnet) for demonstration
- Pure PydanticAI option via client2.py (no Anthropic library dependency)
- Works with any function‑calling LLM in the pure Pydantic variant
Clone the repo, run uv sync, change into mcp-client, then run either client.py (requires OpenAI and Anthropic API keys and uses Anthropic libraries directly) or client2.py (uses only PydanticAI and works with any function‑calling LLM). Export OPENAI_API_KEY and ANTHROPIC_API_KEY before running.
Sample to show to integrate MCP (Model Context Protocol) servers with Pydantic.AI
Parts of this example uses content from : https://github.com/modelcontextprotocol/quickstart-resources.git - Esp. the weather 'server' code
Code uses two different LLMs just for demonstration. The Proxy Agent uses gpt-4o and the tool uses sonnet.
So, export OPENAI_API_KEY as well as ANTHROPIC_API_KEY - OR - modify the code to suit your models
The pyproject.toml assumes you are using 'uv' package manager
Steps to run
1. Clone this repo 1. uv sync 3. cd mcp-client 2. uv run client.py (this requires openai and anthropic keys and uses anthropic libs directly) 2. uv run client2.py (for pure pydantic and works with any fn calling LLM)(Alternatively try client2.py - this uses only PydanticAI - no direct dep on Anthropic libs)
Now, try interacting with some questions like:
> What is the time in NY when it is 7:30pm in Bangalore?
> What is the Weather currently in Chicago?
(and quit when done)
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