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longevity-genie/gget-mcp

longevity-genie/gget-mcp

🐍 🏠 ☁️ - Bioinformatics toolkit for genomics queries and analysis, wrapping the gget library
在 GitHub 查看 ↗直链 · 无中转页
配置模板(请按你的客户端调整)
claude mcp add gget-mcp -- npx -y gget-mcp
这是根据仓库名生成的可粘贴骨架,命令行参数与包名请以该项目 README 为准。
★ 数取值
33 ★ · longevity-genie/gget-mcp · 取自该仓库的 GitHub 页面 · (2026-10-16 20:00:20 核对)
来源明细
收录自 punkpeye/awesome-mcp-servers 榜单(我们从中收集的条目之一) · 条目类型:MCP 服务
收录与活跃
收录于 2026-10-09 · 最近见到 2026-10-16 · 共见到 32 次 · 被 10 个来源列出
评分构成
综合分 1,003 · 33 ★ · 10 个来源 · mcp
常见问题(答案都来自我们的记录)
怎么安装?
我们【没有】从该仓库取到安装命令(我们的 install 覆盖率只有约 4%)。请看它的 README 或 releases 页。
它适合谁 / 用来做什么?
我们把它归在这些标签下: MCP 服务。标签来自条目自身,不是我们强加的分类。
谁维护它、还在更新吗?
仓库 longevity-genie/gget-mcp;我们收录于 2026-10-09;最近见到 2026-10-16。这里没有"官方认证"或"质量评级"——我们只记录来源与时间。
第三方质量标记

gget-mcp

以下摘录自该仓库的 README(片段) · 在 GitHub 读完整 README →

MCP (Model Context Protocol) server for the gget bioinformatics library.
This server implements the Model Context Protocol (MCP) for gget, providing a standardized interface for accessing powerful bioinformatics tools and databases. MCP enables AI assistants and agents to perform complex genomics queries through structured interfaces.
The gget bioinformatics toolkit provides efficient querying of genomic databases and includes functions for:
- Gene and sequence information retrieval
- BLAST and sequence alignment
- Protein structure prediction
- Gene expression analysis
- Functional enrichment analysis
- And much more!
🚀 Quick Example: What Can You Do?
See how the gget MCP server works in practice with AI assistants
**👤 User:** "Analyze the TP53 gene - find its details and protein sequence, then check for cancer mutations"
**🤖 AI Assistant:** I'll help you analyze TP53 step by step:
*[Uses gget_search]* → Found TP53 (ENSG00000141510) on chromosome 17
*[Uses gget_info]* → TP53 is a protein-coding tumor suppressor gene
*[Uses gget_seq with translate=True]* → Retrieved 393 amino acid protein sequence
*[Uses gget_cosmic]* → Found hotspot mutations R175H, R248Q, R273H in multiple cancers
**👤 User:** "Now predict the 3D structure of this protein sequence: MSKGEELFTGVVPILVEL..."
**🤖 AI Assistant:** Let me analyze this sequence:
*[Uses gget_blast]* → Identified as Green Fluorescent Protein (GFP)
*[Uses gget_alphafold]* → Predicted classic beta-barrel structure with 90%+ confidence
**👤 User:** "Perform pathway enrichment for DNA repair genes: TP53, BRCA1, BRCA2, ATM"
**🤖 AI Assistant:** *[Uses gget_enrichr]* → Top pathways: DNA Damage Response, Homologous Recombination, Cell Cycle Checkpoints, p53 Signaling
**See how powerful this is?** You can now ask natural language questions about genes, sequences, mutations, and pathways - the AI does the complex bioinformatics work for you!
About MCP (Model Context Protocol)
Learn more about the Model Context Protocol
MCP is a protocol that bridges the gap between AI systems and specialized domain tools. It enables:
- **Structured Access**: Direct connection to powerful bioinformatics tools and databases
- **Natural Language Queries**: Simplified interaction with complex genomics workflows
- **Type Safety**: Strong typing and validation through FastMCP
- **AI Integration**: Seamless integration with AI assistants and agents
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 or search for MCP videos on YouTube.
Available Tools
Comprehensive bioinformatics functionality through gget
Gene Information & Search
- **gget_search**: Find Ensembl IDs associated with search terms
- **gget_info**: Fetch detailed information for Ensembl IDs
- **gget_seq**: Retrieve nucleotide or amino acid sequences
- **gget_ref**: Get reference genome information from Ensembl
Sequence Analysis
- **gget_blast**: BLAST nucleotide or amino acid sequences
- **gget_blat**: Find genomic locations of sequences
- **gget_muscle**: Align multiple sequences
Expression & Functional Analysis
- **gget_archs4**: Get gene expression data from ARCHS4
- **gget_enrichr**: Perform gene set enrichment analysis
Protein Structure & Function
- **gget_pdb**: Fetch protein structure data from PDB
- **gget_alphafold**: Predict protein structure using AlphaFold
Cancer & Mutation Analysis
- **gget_cosmic**: Search COSMIC database for cancer mutations
Single-cell Analysis
- **gget_cellxgene**: Query single-cell RNA-seq data from CellxGene
Quick Start
Installing uv (optional - uvx can auto-install)
uvx is a very nice tool that can run a python package installing it if needed.
Running with uvx
You can run the gget-mcp server directly using uvx without cloning the repository:
Other uvx modes (STDIO, HTTP, SSE)
STDIO Mode (for MCP clients that require stdio)
HTTP Mode (Web Server)
SSE Mode (Server-Sent Events)
In cases when there are problems with uvx often they can be caused by cleaning uv cache:
The HTTP mode will start a web server that you can access at http://localhost:3002/mcp (with documentation at http://localhost:3002/docs). The STDIO mode is designed for MCP clients that communicate via standard input/output, while SSE mode uses Server-Sent Events for real-time communication.
来源
awesome · https://github.com/longevity-genie/gget-mcp
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