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Enrichr MCP Server

@tianqitang1

Repository

Basic information

Category

Other

Transports

stdio

Author

tianqitang1

About Enrichr MCP Server

No overview available yet

Enrichr MCP Server 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"
      ]
    }
  }
}

Enrichr MCP Server tools

2

Perform gene set enrichment analysis using Enrichr across multiple gene set libraries. Returns only statistically significant terms (adjusted p < 0.05). Configured default libraries: - GO_Biological_Process_2025: Gene Ontology terms describing biological objectives accomplished by gene products. Any library in Enrichr's live catalog is accepted. Enrichr adds and retires libraries continuously, so do not rely on a memorized list: call suggest_libraries, or read the enrichr://libraries resource, to discover the libraries that currently exist. Pass 'background' to test against a custom background gene set (for example, only the genes expressed in your assay) instead of Enrichr's whole-genome default. This is the statistically correct choice whenever the gene list was drawn from a restricted universe, and it matters: the whole-genome default can overstate significance by many orders of magnitude. Each library's result reports 'backgroundCorrected'. If Enrichr's background service is unavailable the result falls back to uncorrected whole-genome p-values, flagged with a warning — treat those numbers as inflated and re-run rather than reporting them as background-corrected.

Suggest relevant Enrichr libraries for a research question. Use this before enrichr_analysis to pick the best libraries for a specific topic.

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

Frequently asked questions

1

What runtime is required?

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

2

Where does the enrichment data come from?

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

3

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.

4

Are results filtered before returning?

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

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