PubMed MCP

# PubMed MCP PubMed MCP exposes the PubMed E-Utilities search workflow over HTTP so it can be consumed by clients that implement the Model Context Protocol (MCP) or any other REST-capable integration. It provides a single endpoint for querying PubMed and returns curated article metadata in a consistent JSON shape. ## Features - 🔎 Search PubMed with a single HTTP request. - 📄 Retrieves article summaries (title, journal, publication date, authors, DOI, and canonical URL). - 🛠️ Configurable via environment variables, including an optional NCBI API key for higher rate limits. - 🧪 Tested with mocked responses to ensure resilient parsing of PubMed responses. ## Getting started ### 1. Install dependencies Create and activate a Python 3.10+ environment, then install the dependencies: ```bash pip install -e . # For development and testing extras pip install -e .[dev] ``` ### 2. (Optional) Configure an API key Set `PUBMED_API_KEY` or `NCBI_API_KEY` with your NCBI E-Utilities API key to unlock higher throughput. ```bash export PUBMED_API_KEY="your-api-key" ``` ### 3. Launch the HTTP server Run the FastAPI app with Uvicorn: ```bash uvicorn pubmed_mcp.server:app --host 0.0.0.0 --port 8000 # or python -m pubmed_mcp.main ``` You can now query the service: ```bash curl "http://localhost:8000/articles/search?q=heart+disease&limit=5" ``` ### 4. Run the test suite ```bash pytest ``` ## API - `GET /health` – Returns `{ "status": "ok" }` for readiness checks. - `GET /articles/search` – Required query parameter `q`; optional `limit` (default `10`, max `50`). Returns a JSON payload containing the original query, the applied limit, and a list of article summaries. ## Development notes - The `PubMedClient` handles eSearch and eSummary requests and merges them into a list of `ArticleSummary` dataclasses. - The FastAPI app caches a single client instance and gracefully closes it during shutdown. - Tests use `respx` to simulate PubMed responses, keeping the suite fast and deterministic.