MCP for OpenGenes
Wellknown found it in public sources; nobody has proven control of it yet. Claiming takes one click if the repository is under your GitHub account, or a small file on your domain otherwise. Verified owners get the badge, 15-minute checks, status alerts, edits that outrank crawled data, and a ranking boost.
Agents can do it too: POST https://wellknown.network/api/v1/claims with {"agent":"opengenes-mcp","method":"well_known_file"} — machine-readable steps at claim.json, guide at /docs/claim.
Everything here was measured by our prober or read from a registry. Nothing is self-reported.
Attributed to the source that supplied each field. Treated as claims, not facts.
# opengenes-mcp [](https://github.com/longevity-genie/opengenes-mcp/actions/workflows/test.yml) [](https://badge.fury.io/py/opengenes-mcp) [](https://www.python.org/downloads/) [](https://opensource.org/licenses/MIT) [](https://github.com/psf/black) MCP (Model Context Protocol) server for OpenGenes database This server implements the Model Context Protocol (MCP) for OpenGenes, providing a standardized interface for accessing aging and longevity research data. MCP enables AI assistants and agents to query comprehensive biomedical datasets through structured interfaces. The server automatically downloads the latest OpenGenes database and documentation from [Hugging Face Hub](https://huggingface.co/longevity-genie/bio-mcp-data) (specifically from the `opengenes` folder), ensuring you always have access to the most up-to-date data without manual file management. The OpenGenes database contains: - **lifespan_change**: Experimental data about genetic interventions and their effects on lifespan across model organisms - **gene_criteria**: Criteria classifications for aging-related genes (12 different categories) - **gene_hallmarks**: Hallmarks of aging associated with specific genes - **longevity_associations**: Genetic variants associated with longevity from population studies If you want to understand more about what the Model Context Protocol is and how to use it more efficiently, you can take the [DeepLearning AI Course](https://www.deeplearning.ai/short-courses/mcp-build-rich-context-ai-apps-with-anthropic/) or search for MCP videos on YouTube. ## 🏆 Part of Holy Bio MCP Framework This MCP serv…
Mapped onto the structured taxonomy from declared text and observed tool names. Confidence shown for derived entries.
Every source is kept verbatim. Field changes are logged as events.