Skip to main content
Glama

@pipeworx/gprofiler

Functional enrichment for a gene list against GO, KEGG, Reactome, WikiPathways, TRANSFAC, miRTarBase, CORUM, HPA and HPO, plus gene/protein identifier conversion and cross-species ortholog mapping — from g:Profiler at the University of Tartu.

Part of Pipeworx — an MCP gateway connecting AI agents to 1679+ live data sources.

Tools

  • gprofiler_enrich(organism, query[], sources?, user_threshold?, no_iea?, ordered?, domain_scope?, background?, significant?, limit?) — g:GOSt. Returns each enriched term with an ALREADY-ADJUSTED p-value (g:SCS), term size, query size, overlap, precision and recall. Per-gene intersections and ontology parents are dropped: they dominate the payload and nothing reads them in an answer.

  • gprofiler_convert_ids(organism, query[], target?, numeric_namespace?) — g:Convert. Maps between gene/protein/transcript/probe namespaces and reports hitsForInput, so an ambiguous symbol shows up as ambiguous instead of quietly resolving to one gene.

  • gprofiler_orthologs(organism, target, query[]) — g:Orth via Ensembl Compara. Human TP53 → mouse Trp53, with one-to-many mappings flagged rather than collapsed.

Related MCP server: KEGG MCP Server

Auth

Keyless. g:Profiler asks programmatic callers to identify themselves; the pack sends a pipeworx-mcp-gprofiler User-Agent.

Data sources

  • POST https://biit.cs.ut.ee/gprofiler/api/gost/profile/ — enrichment.

  • POST https://biit.cs.ut.ee/gprofiler/api/convert/convert/ — ID conversion.

  • POST https://biit.cs.ut.ee/gprofiler/api/orth/orth/ — orthologs.

  • Docs: https://biit.cs.ut.ee/gprofiler/page/apis

Traps

The organism code is g:Profiler's own and nothing else works. First letter of the genus plus the full species name, lowercase: hsapiens, mmusculus, rnorvegicus, drerio, dmelanogaster, celegans, scerevisiae, athaliana. "human" and "9606" are both rejected. This is the common first failure, and it is a loud one, which is the good case.

A single gene passed as a bare string would be split into characters upstream. The pack accepts a string and splits it on whitespace/comma/semicolon before sending, so "TP53" becomes ["TP53"] rather than four failed lookups returned as a clean 200.

An empty enrichment result is ambiguous and the pack says so. No significant term is a real answer for a small or functionally unrelated list — and it is also exactly what a wrong organism code or unrecognised identifiers produce. The note field points the caller at gprofiler_convert_ids to tell the two apart.

pValue is already multiple-testing corrected (g:SCS by default). Do not correct it again.

n_incoming > 1 on a conversion means the INPUT matched more than one record, not that the output is multi-valued. Surfaced as hitsForInput and collected in ambiguousInputs.

Enrichment against all sources on a large list is genuinely slow (seconds, not milliseconds). Pass sources when you know which annotation set you want.

Quick Start

Add to your MCP client (Claude Desktop, Cursor, Windsurf, etc.):

{
  "mcpServers": {
    "gprofiler": {
      "url": "https://gateway.pipeworx.io/gprofiler/mcp"
    }
  }
}

What this endpoint actually serves

tools/list at https://gateway.pipeworx.io/gprofiler/mcp returns the tools in the table above plus the shared Pipeworx meta-tools — ask_pipeworx, discover_tools, search_within, remember/recall and the rest of the gateway-wide set. So the tool count you see is larger than this table: a single-pack endpoint currently lists roughly 30 shared tools alongside the pack's own. The connection's initialize response states its exact scope, and is the authoritative answer for a given day.

This is deliberate, not multiplexing by accident. The meta-tools are what let a scoped connection answer a question this pack does not cover — via ask_pipeworx, which routes across the whole catalog — without you adding a second MCP server. There is currently no way to mount a pack endpoint without them; if the extra schemas cost you more context than the routing is worth, connect to the full gateway once rather than to several pack endpoints.

Or connect to the full Pipeworx gateway to get every pack's tools listed directly, instead of just this one's:

{
  "mcpServers": {
    "pipeworx": {
      "url": "https://gateway.pipeworx.io/mcp"
    }
  }
}

Both URLs reach the same gateway and the same 1679+ data sources. The only difference is which pack's tools are listed directly; ask_pipeworx reaches all of them from either one.

No MCP client? Call it over HTTP

curl -X POST https://gateway.pipeworx.io/v1/tools/gprofiler_enrich \
  -H 'Content-Type: application/json' \
  -d '{"organism":"hsapiens","query":["TP53","BRCA1","BRCA2","ATM","CHEK2","PALB2"],"sources":["REAC"],"limit":5}'

No account needed for the first calls. Inspect any tool: GET https://gateway.pipeworx.io/v1/tools/gprofiler_enrich. Find one: POST https://gateway.pipeworx.io/v1/tools/search_packs with {"query":"..."}.

Standalone (no gateway account)

This package also runs as a local stdio MCP server — no Pipeworx account, no gateway round-trip:

{
  "mcpServers": {
    "gprofiler": {
      "command": "npx",
      "args": ["-y", "@pipeworx/mcp-gprofiler"]
    }
  }
}

Or run it directly to confirm it starts:

npx -y @pipeworx/mcp-gprofiler

It speaks MCP over stdin/stdout and answers initialize/tools/list/tools/call for only this pack's tools — none of the shared meta-tools the gateway connection above adds. Same source, same tools, no ask_pipeworx routing.

Using with ask_pipeworx

Instead of calling tools directly, you can ask questions in plain English — this works on the pack endpoint above as well as on the full gateway:

ask_pipeworx({ question: "your question about Gprofiler data" })

The gateway picks the right tool and fills the arguments automatically.

More

License

MIT

Related MCP Connectors

Related MCP Servers

  • A
    license
    B
    quality
    C
    maintenance
    Provides access to the STRING protein-protein interaction database for mapping identifiers, retrieving interaction networks, and performing functional enrichment analysis. It enables users to explore protein partners, pathways, and cross-species homology through natural language interactions.
    9
    1
    ISC
  • A
    license
    A
    quality
    A
    maintenance
    ▎ Provides 32 tools for plant-genomics locus lookup across 11 free public backends (Ensembl Plants, Phytozome, UniProtKB, Europe PMC, QuickGO, NCBI BLAST, Gramene, KEGG, STRING-DB, ATTED-II, BAR). Takes a TAIR-style locus plus optional organism and returns gene metadata, functional/pathway annotation, interactions, co-expression, and literature — in single-locus, batch, and cross-source synthesis.
    53
    62 PyPI
    6
    MIT
  • A
    license
    A
    quality
    D
    maintenance
    Enables coding agents to interact with the Reactome pathway database, including search, lookup, hierarchy traversal, SBML/SBGN export, and gene-set enrichment analysis.
    17
    MIT