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Analyze polygenic risk scores with catalog search, normalization, and risk estimation.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "just-prs-mcp" yet — see the docs or source repo.
Search for polygenic risk score models related to type 2 diabetes, and list available catalog entries, target populations, and key characteristics.
A list of relevant PRS models with sources, target populations, and filtering details.
Use the provided VCF sample and selected PRS model to compute a polygenic risk score, then output the raw score, percentile, and risk interpretation.
A PRS result including score, population percentile, and risk-level interpretation.
First normalize this VCF, then assess whether it is suitable for PRS analysis, and provide a quality evaluation with potential issues.
Normalized VCF processing results plus a pre-PRS quality assessment and issue summary.
Access biological databases for GWAS, proteins, variants, and drug discovery with AI.
Annotate whole-genome VCFs and query pharmacogenomics and disease risk in natural language.
Calculate a patient's 10-year ASCVD risk from demographics and clinical factors.
Access multiple biomedical MCP data services through one unified endpoint.
Connect to Jupyter via MCP to run code and explore data interactively.
Turn CVs and projects into MCP tools for querying and job matching.