Enrichr MCP Server
@tianqitang1
关于 Enrichr MCP Server
暂无概览
基本信息
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
未检测到工具
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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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