MCP-compliant API server enabling AI models to programmatically search and retrieve proteomics datasets from the PRIDE Archive using keyword, date, and popularity filters for advanced biomedical research.
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This project implements a Model Context Protocol (MCP)-compliant API server that exposes tools to search the PRIDE Archive, a major repository for proteomics data. It allows AI models (such as Claude or other MCP-compatible LLMs) to interact with proteomics datasets programmatically using structured function calling.
FastMCP
http
(SSE) and stdio
connection modesClone the repo and install dependencies:
git clone https://github.com/PRIDE-Archive/mcp_pride_archive_search.git cd mcp_pride_archive_search poetry install # or pip install -r requirements.txt
Start the MCP server with your preferred connection type (http or stdio):
python -m mcp_pride_archive_search --connection_type http --port 9999
Command-line Arguments
Argument | Description | Default |
---|---|---|
--connection_type | Type of connection: http or stdio | http |
--port | Port to run the server (for HTTP mode) | 9999 |
Fetches proteomics datasets from the PRIDE Archive database.
Use this when:
This server works with any LLM that supports Model Context Protocol, including:
+---------------------+ Tool Calls +-----------------------------+ | Claude / Gemini AI | | MCP PRIDE API Server | +---------------------+ | - search_archive_tool() | | - server_status() | +-----------------------------+ | v +---------------------------+ | PRIDE Archive REST API | | (https://www.ebi.ac.uk | | /pride/ws/archive/ | | v3/search/projects) | +---------------------------+
MIT License. See LICENSE for details.
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