Enrichr MCP Server

Name: Enrichr MCP Server
Author: tianqitang1

@tianqitang1

Repository

About Enrichr MCP Server

No overview available yet

Basic information

Config

Add this server to your MCP-compatible client using the configuration below.

{
  "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"
      ]
    }
  }
}

Tools

No tools detected

We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.

Overview

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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