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Enrichr MCP Server

@tianqitang1

关于 Enrichr MCP Server

暂无概览

基本信息

分类

其他

运行时

node

传输方式

stdio

发布者

tianqitang1

配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

{
  "mcpServers": {
    "enrichr-go-only": {
      "command": "npx",
      "args": [
        "-y",
        "enrichr-mcp-server",
        "--libraries",
        "GO_Biological_Process_2025"
      ]
    },
    "enrichr-pathways": {
      "command": "npx",
      "args": [
        "-y",
        "enrichr-mcp-server",
        "-l",
        "GO_Biological_Process_2025,KEGG_2021_Human,Reactome_2022"
      ]
    },
    "enrichr-disease": {
      "command": "npx",
      "args": [
        "-y",
        "enrichr-mcp-server",
        "--libraries",
        "Human_Phenotype_Ontology,OMIM_Disease,ClinVar_2019"
      ]
    }
  }
}

工具

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概览

What is Enrichr MCP Server?

A Model Context Protocol (MCP) server that provides gene set enrichment analysis using the Enrichr API. It supports hundreds of gene set libraries and returns only statistically significant results (adjusted p < 0.05) to reduce context usage.

How to use Enrichr MCP Server?

Install globally via npx -y enrichr-mcp-server and configure in your MCP client (e.g., .cursor/mcp.json). Use the enrichr_analysis tool for multi-library enrichment, or the query_enrichr_go_bp_tool / go_enrichment tools for GO Biological Process analysis. Custom default libraries can be set via CLI arguments (--libraries) or the ENRICHR_DEFAULT_LIBRARIES environment variable.

Key features of Enrichr MCP Server?

  • Multi-library enrichment analysis with simultaneous queries
  • Significance filtering (adjusted p < 0.05)
  • Detailed results with p-values, z-scores, and combined scores
  • Hundreds of gene set libraries supported
  • Robust error handling with informative messages
  • Specialized GO Biological Process tool

Use cases of Enrichr MCP Server

  • Analyze cancer gene lists for enriched pathways and GO terms
  • Discover disease associations using phenotype libraries (HPO, OMIM)
  • Identify transcription factor targets from ChEA and ENCODE
  • Evaluate drug-gene interactions via DrugMatrix and L1000
  • Investigate microRNA targets using TargetScan and miRTarBase

FAQ from Enrichr MCP Server

What runtime is required?

Node.js 18+ and an internet connection for Enrichr API access.

Where does the enrichment data come from?

All results are fetched in real‑time from the public Enrichr API (https://maayanlab.cloud/Enrichr/).

Can I specify which libraries to use?

Yes, you can set default libraries via the --libraries CLI argument or the ENRICHR_DEFAULT_LIBRARIES environment variable.

Are results filtered before returning?

Yes, only terms with an adjusted p-value < 0.05 are returned

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