home / mcp / pydantic ai docs mcp server
Provides programmatic access to Pydantic AI documentation, including cloning/updating docs, retrieving specific documents, listing topics, and viewing changelogs.
Configuration
View docs{
"mcpServers": {
"omniwaifu-pydantic-ai-docs-server": {
"command": "uv",
"args": [
"--directory",
"/path/to/your/pydantic-ai-docs-server",
"run",
"-m",
"pydantic_ai_docs_server"
]
}
}
}You can access and control the Pydantic AI documentation through an MCP server. This setup lets you clone or update the docs, fetch specific documents, list topics, and view changelogs programmatically, all via standardized MCP tools. This makes it easy to integrate docs data into your apps or workflows.
Use an MCP client to discover the available tools and then call them to interact with the documentation data. The server operates over a standard input/output channel, accepting JSON requests and returning JSON responses. Key capabilities include updating the documentation repository, retrieving a document by path, listing docs topics, and accessing changelogs.
Prerequisites: Python 3.12 or newer, and a tool for running the MCP server (uv) or a Python environment you can activate.
Clone this project and enter the directory.
Create and activate a Python virtual environment.
python -m venv .venv
source .venv/bin/activate # On Windows use: .venv\Scripts\activateInstall dependencies in editable mode so you can run and develop locally.
uv pip install -e .
# Or, if you don't have uv:
# pip install -e .Run the server after installation. You can start it by running the module directly or by using the installed script. The server is designed to communicate over stdio using newline-delimited JSON messages, making it straightforward to integrate with MCP clients.
Clones the documentation repository if not present or pulls the latest updates. If force_clone is true, it deletes the existing repository and clones it anew.
Retrieves a specific documentation file by its path relative to the docs directory, for example usage/models.md.
Lists files and directories within the docs directory. If a path is provided, lists contents of that subdirectory.
Lists all changelog files found under the docs history folder in the repository.
Retrieves the content of a specific changelog file, such as history/0.2.0.md.