Enrichr MCP Server

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

Use the button below to install the MCP server to Cursor with default settings (GO Biological Process only).

Features

• Multi-Library Enrichment Analysis: Query multiple Enrichr libraries simultaneously (GO, pathways, diseases, tissues, drugs, etc.)
• GO Enrichment Analysis: Specialized tools for GO Biological Process enrichment analysis
• Comprehensive Library Support: Access to hundreds of gene set libraries including:
  • Gene Ontology (Biological Process, Molecular Function, Cellular Component)
  • Pathway databases (KEGG, Reactome, WikiPathways, BioCarta, MSigDB)
  • Disease/Phenotype databases (Human Phenotype Ontology, GWAS Catalog)
  • Tissue/Cell type libraries (GTEx, Human Cell Atlas, ARCHS4)
  • Drug/Chemical libraries (DrugMatrix, L1000, TG-GATEs)
  • Transcription Factor targets (ChEA, ENCODE)
  • MicroRNA targets (TargetScan, miRTarBase)
• Significance Filtering: Returns only terms with adjusted p < 0.05 to reduce noise
• Detailed Results: Provides p-values, z-scores, combined scores, and overlapping genes
• Error Handling: Robust error handling with informative messages

Configuration

MCP Client Configuration

Add this server to your MCP client configuration (e.g., .cursor/mcp.json):

Basic Configuration (GO Biological Process only)

{
  "mcpServers": {
    "enrichr-server": {
      "command": "npx",
      "args": ["-y", "enrichr-mcp-server"]
    }
  }
}

Custom Default Libraries Configuration

You can configure default libraries using CLI arguments in your MCP configuration:

{
  "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"]
    }
  }
}

Environment Variables Configuration

Alternatively, use environment variables:

{
  "mcpServers": {
    "enrichr-server": {
      "command": "npx",
      "args": ["-y", "enrichr-mcp-server"],
      "env": {
        "ENRICHR_DEFAULT_LIBRARIES": "GO_Biological_Process_2025,KEGG_2021_Human",
        "ENRICHR_SERVER_NAME": "my-enrichr-server"
      }
    }
  }
}

Command Line Options

# Show help
npx enrichr-mcp-server --help

# Use only GO Biological Process
npx enrichr-mcp-server --libraries "GO_Biological_Process_2025"

# Use multiple libraries (comma-separated)  
npx enrichr-mcp-server -l "GO_Biological_Process_2025,KEGG_2021_Human,MSigDB_Hallmark_2020"

# Set custom server name
npx enrichr-mcp-server --name "my-enrichr-server"

Environment Variables

• ENRICHR_DEFAULT_LIBRARIES: Comma-separated list of default libraries
• ENRICHR_SERVER_NAME: Custom server name

Benefits of Default Library Configuration

1. Simplified Tool Calls: When libraries aren't specified in tool calls, your configured defaults are used
2. Consistent Results: Ensures consistent library usage across different queries
3. Multiple Configurations: Set up different MCP server instances for different research contexts
4. Override Capability: Individual tool calls can still specify different libraries when needed

Usage

The server provides three tools:

enrichr_analysis (Recommended for multi-library analysis)

Performs enrichment analysis across multiple specified Enrichr libraries.

Parameters:

• genes (required): Array of gene symbols (e.g., ["TP53", "BRCA1", "EGFR"])
• libraries (optional): Array of Enrichr library names to query (defaults to ["GO_Biological_Process_2025"])
• description (optional): Description for the gene list (default: "Gene list for enrichment analysis")

Popular Libraries:

• Gene Ontology: GO_Biological_Process_2025, GO_Molecular_Function_2025, GO_Cellular_Component_2025
• Pathways: KEGG_2021_Human, Reactome_2022, WikiPathways_2023_Human, MSigDB_Hallmark_2020
• Disease/Phenotype: Human_Phenotype_Ontology, GWAS_Catalog_2023, ClinVar_2019
• Tissue/Cell Types: GTEx_Tissue_Sample_Gene_Expression_Profiles_up, Human_Gene_Atlas, ARCHS4_Tissues
• Transcription Factors: ChEA_2022, ENCODE_TF_ChIP-seq_2015, TRANSFAC_and_JASPAR_PWMs
• MicroRNA: TargetScan_microRNA_2017, miRTarBase_2017
• Drugs: DrugMatrix, L1000_Kinase_and_GPCR_Perturbations_up, TG_GATEs_2019

Example:

{
  "name": "enrichr_analysis",
  "arguments": {
    "genes": ["TP53", "BRCA1", "EGFR", "MYC", "AKT1"],
    "libraries": [
      "GO_Biological_Process_2025",
      "KEGG_2021_Human", 
      "MSigDB_Hallmark_2020",
      "Human_Phenotype_Ontology"
    ],
    "description": "Cancer-related genes"
  }
}

query_enrichr_go_bp_tool

Performs GO Biological Process enrichment analysis (legacy tool for backward compatibility).

Parameters:

• genes (required): Array of gene symbols (e.g., ["TP53", "BRCA1", "EGFR"])
• description (optional): Description for the gene list (default: "Gene list for GO BP enrichment")

Example:

{
  "name": "query_enrichr_go_bp_tool",
  "arguments": {
    "genes": ["TP53", "BRCA1", "EGFR"],
    "description": "Cancer-related genes"
  }
}

go_enrichment

Alternative name for query_enrichr_go_bp_tool with more intuitive naming.

Returns: All tools return formatted text with significant terms including:

• Library name and summary statistics
• Term name and identifier
• Adjusted P-value and raw P-value (scientific notation)
• Odds ratio and combined score
• Overlapping genes with counts

Available Library Categories

Enrichr contains hundreds of gene set libraries organized into categories:

• Gene Ontology: Biological processes, molecular functions, cellular components
• Pathways: KEGG, Reactome, WikiPathways, BioCarta, NCI, HumanCyc, Panther
• Disease/Phenotype: HPO, OMIM, ClinVar, GWAS Catalog, DisGeNET
• Tissues/Cell Types: GTEx, Human Cell Atlas, ARCHS4, Mouse Gene Atlas
• Transcription Factors: ChEA, ENCODE, TRANSFAC, JASPAR
• MicroRNA Targets: TargetScan, miRTarBase, microRNA.org
• Drug/Chemical: DrugMatrix, L1000, TG-GATEs, CTD
• Protein Interactions: BioGRID, STRING, hu.MAP
• Literature Mining: PubMed, Geneshot, Co-expression
• Evolutionary: Cross-species homologs, phylogenetic profiles

For a complete list of available libraries, visit the Enrichr Libraries page.

API Details

This server uses the Enrichr API:

• Add List Endpoint: https://maayanlab.cloud/Enrichr/addList
• Enrichment Endpoint: https://maayanlab.cloud/Enrichr/enrich
• Supported Libraries: All libraries available through Enrichr web interface

Development

• Build: npm run build
• Watch: npm run watch (rebuilds on file changes)
• Inspector: npm run inspector (debug with MCP inspector)

Requirements

• Node.js 18+
• TypeScript 5.3+
• Internet connection for Enrichr API access

License

This project follows the same license as the MCP TypeScript SDK.

References

• Chen EY, Tan CM, Kou Y, Duan Q, Wang Z, Meirelles GV, Clark NR, Ma'ayan A. Enrichr: interactive and collaborative HTML5 gene list enrichment analysis tool. BMC Bioinformatics. 2013; 128(14).

• Kuleshov MV, Jones MR, Rouillard AD, Fernandez NF, Duan Q, Wang Z, Koplev S, Jenkins SL, Jagodnik KM, Lachmann A, McDermott MG, Monteiro CD, Gundersen GW, Ma'ayan A. Enrichr: a comprehensive gene set enrichment analysis web server 2016 update. Nucleic Acids Research. 2016; gkw377.

• Xie Z, Bailey A, Kuleshov MV, Clarke DJB., Evangelista JE, Jenkins SL, Lachmann A, Wojciechowicz ML, Kropiwnicki E, Jagodnik KM, Jeon M, & Ma'ayan A. Gene set knowledge discovery with Enrichr. Current Protocols, 1, e90. 2021. doi: 10.1002/cpz1.90

• Enrichr

• Model Context Protocol

• MCP TypeScript SDK