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longevity-genie/opengenes-mcp

by Various

MCP for the open-genes

L

MCP

longevity-genie/opengenes-mcp

Added 1 June 2026

Overview

An MCP (Model Context Protocol) server that provides access to open-genes data, enabling AI agents to query gene information programmatically. Built in Python, it serves as a bridge between large language models and open-genes datasets.

Best for

Best for
Developers building AI assistants or agents that need to query open-genes gene data for longevity research

Use cases

  • Query gene metadata and annotations from open-genes through an MCP interface
  • Integrate longevity-related gene data into AI agent workflows
  • Extend AI chatbots with factual gene information retrieval capabilities

How to use

Install

uvx opengenes-mcp

Tools exposed

  • opengenes_db_query
  • opengenes_get_schema_info
  • opengenes_example_queries

Tested with

Claude Desktop, Cursor, Windsurf, VS Code

Example client config

{\n  "mcpServers": {\n    "opengenes-mcp": {\n      "command": "uvx",\n      "args": ["opengenes-mcp"],\n      "env": {\n        "MCP_TRANSPORT": "stdio"\n      }\n    }\n  }\n}

Notes

An MCP (Model Context Protocol) server that provides access to open-genes data, enabling AI agents to query gene information programmatically. Built in Python, it serves as a bridge between large language models and open-genes datasets.

18 stars on GitHub. Last updated 2025-10-14. Licensed MIT.

Use cases

  • Query gene metadata and annotations from open-genes through an MCP interface
  • Integrate longevity-related gene data into AI agent workflows
  • Extend AI chatbots with factual gene information retrieval capabilities

Pros

  • Leverages the standard MCP protocol for easy integration with AI tools
  • Python-based, making it straightforward to customize or extend
  • Open source with a clear focus on longevity and gene data

Cons

  • Small community (18 stars) may mean limited support or contributions
  • Narrow scope limited to open-genes, not a general-purpose knowledge base
  • Requires running a local MCP server, adding deployment overhead

Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.

Pros

  • Leverages the standard MCP protocol for easy integration with AI tools
  • Python-based, making it straightforward to customize or extend
  • Open source with a clear focus on longevity and gene data

Cons

  • Small community (18 stars) may mean limited support or contributions
  • Narrow scope limited to open-genes, not a general-purpose knowledge base
  • Requires running a local MCP server, adding deployment overhead
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