How do I install and configure GWAS-MCP?

Installation is straightforward via `pip install gwas-mcp`. You then configure it by adding a simple command and arguments to your Claude Desktop configuration file to integrate the MCP server.

What types of data can I explore with GWAS-MCP?

You can explore comprehensive protein and gene data (UniProt, NCBI), clinical variants (ClinVar, GWAS Catalog), protein interactions (STRING), structures (AlphaFold, PDB), pathways (KEGG), drug targets (Open Targets), and genetic diseases (OMIM).

How does GWAS-MCP integrate with AI?

It functions as an MCP server, enabling AI clients like Claude Desktop to use its vast array of tools and databases through natural language queries, facilitating AI-driven data retrieval and analysis.

What are the primary use cases for GWAS-MCP?

GWAS-MCP is ideal for genomics research, clinical variant interpretation, protein interaction analysis, structural biology, drug target validation, pharmacogenomics, and understanding genetic diseases.

GWAS

Name: GWAS
Author: zaeyasa

byzaeyasa

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データサイエンスとML

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分析と監視

Integrate AI-powered access to major biological databases for genomics and bioinformatics research through a Model Context Protocol server.

GWAS-MCP is a powerful Model Context Protocol (MCP) server designed to bridge bioinformatics and genomics research with AI capabilities. It seamlessly integrates with MCP clients like Claude Desktop, providing AI-powered access to a vast array of over 30 tools across 12 major biological databases. Researchers can leverage this server for comprehensive protein and gene lookups, clinical variant analysis, exploration of protein interactions and networks, investigation of structures and pathways, drug discovery, and insights into genetic diseases, all enhanced by smart caching and asynchronous operations for optimal performance.

主な機能

01AI-powered access to over 30 bioinformatics tools and 12 major biological databases.

02Comprehensive protein and gene lookup from UniProt, Ensembl, and NCBI Gene.

03Detailed clinical variant interpretations via ClinVar and GWAS Catalog queries.

04Exploration of protein interactions, structures, and metabolic pathways using STRING, AlphaFold, PDB, and KEGG.

05Tools for drug target validation, disease associations, and pharmacogenomics through Open Targets and PharmGKB.

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ユースケース

01Investigating the pathogenicity of clinical variants and querying genome-wide association studies.

02Retrieving detailed information about specific genes, proteins, or genetic variants.

03Discovering protein-protein interactions, analyzing functional enrichment, and exploring biological pathways.