GenePattern MCP Server

GenePattern MCP Server

Bridge any AI coding assistant directly to GenePattern — run bioinformatics modules, manage cloud jobs, and stream results, all through natural language.

Category
Visit Server

README

<h1 align="center">GenePattern MCP Server</h1>

<div align="center"> <em>Bridge any AI coding assistant directly to GenePattern — run bioinformatics modules, manage cloud jobs, and stream results, all through natural language.</em>

Python License: BSD-3 Powered by GenePattern

</div>


Why GenePattern MCP?

Modern AI assistants are extraordinarily good at reasoning — but they can't run a gene expression pipeline or execute bioinformatics on their own. We built GenePattern MCP to close that gap.

By implementing the Model Context Protocol (MCP), this server exposes the full GenePattern REST API as a set of structured, type-safe tools that any MCP-compatible AI client (Claude, Cursor, GitHub Copilot, and more) can call directly. The result: your AI assistant can now:

  • 🧬 Search, inspect, and execute hundreds of peer-reviewed genomic analysis modules
  • 🤖 Chain bioinformatic tasks into multi-step AI-driven workflows — no manual API calls required
  • ☁️ Scale effortlessly on GenePattern's cloud infrastructure at cloud.genepattern.org
  • 📊 Guarantee reproducibility — every job is tracked by LSID and stored with full provenance

From raw expression data to publication-ready insights — powered by a conversation.


Feature Highlights

Feature Description
🧬 Genomic Integration Access 200+ curated modules: differential expression, pathway analysis, single-cell, proteomics, and more
🤖 AI/ML Workflows Let your LLM orchestrate multi-step pipelines end-to-end via natural language prompts
☁️ Cloud Scalability Jobs run on GenePattern's managed cloud — no local compute needed
📊 Reproducible Science Every module is versioned by LSID; every job is logged and retrievable
🔌 Multi-Transport stdio for local clients, streamable-http / SSE for remote or containerized deployments
🔐 Flexible Auth Pluggable AuthHandler system — env-var token, HTTP Bearer header, or bring your own
🐳 Docker-Ready Official image at genepattern/mcp; zero-config cloud deployment

Prerequisites

  • Python 3.11+
  • A GenePattern API token (see Get a Token below)
  • pip or uv

Installation

With pip:

pip install -r requirements.txt

With uv:

uv venv && source .venv/bin/activate
uv pip install -r requirements.txt

Get a GenePattern Token

You need a Bearer token to authenticate with GenePattern.

Option A — You already have a token:

export GENEPATTERN_KEY="YOUR_TOKEN"

Option B — Generate one with the included helper:

python get-token.py -s https://cloud.genepattern.org/gp \
                    -u YOUR_USERNAME \
                    -p YOUR_PASSWORD
# Follow the printed instructions to export GENEPATTERN_KEY

Quick Start

1. Start the server (local stdio — recommended for AI clients)

export GENEPATTERN_KEY="YOUR_TOKEN"
python server.py --transport stdio

2. Run a bioinformatic analysis via your AI assistant

Once connected, ask your AI assistant something like:

"Run PreprocessDataset on all_aml_test.gct, threshold at 20/1500, and download the result."

The MCP server will:

  1. Look up the PreprocessDataset module LSID automatically
  2. Submit the job to GenePattern cloud
  3. Poll for completion and return the output file paths

3. Explore available tools interactively

mcp dev server.py

Running the Server

The server supports three transport modes via FastMCP.

Mode Command
stdio (local AI clients) python server.py --transport stdio
HTTP (remote / Docker) python server.py --transport streamable-http --host 0.0.0.0 --port 3000
SSE python server.py --transport sse --host 0.0.0.0 --port 3000

Testing with GenePattern Copilot:

python server.py --transport streamable-http --host 0.0.0.0 --port 3000 \
    --auth-handler genepattern_mcp._shared.HeaderAuthHandler

Docker

Pull and run the official image in seconds:

docker pull genepattern/mcp

Run in HTTP mode:

docker run --rm \
  -e GENEPATTERN_URL=https://cloud.genepattern.org/gp \
  -e GENEPATTERN_KEY=YOUR_TOKEN \
  -e FASTMCP_TRANSPORT=streamable-http \
  -e FASTMCP_HOST=0.0.0.0 \
  -e FASTMCP_PORT=3000 \
  -p 3000:3000 \
  genepattern/mcp

Using Authorization header instead of an env token (stateless, multi-user HTTP):

docker run --rm -p 3000:3000 \
  -e AUTH_HANDLER=genepattern_mcp._shared.HeaderAuthHandler \
  -e FASTMCP_TRANSPORT=streamable-http \
  genepattern/mcp
# Clients send: Authorization: Bearer YOUR_TOKEN

Note: stdio transport is impractical inside Docker containers. Use streamable-http when containerized.


Connect from MCP-Enabled Clients

Claude Code (VS Code)

Local stdio (recommended):

{
  "mcpServers": {
    "genepattern": {
      "command": "python",
      "args": ["server.py", "--transport", "stdio"],
      "env": {
        "GENEPATTERN_URL": "https://cloud.genepattern.org/gp",
        "GENEPATTERN_KEY": "${env:GENEPATTERN_KEY}"
      }
    }
  }
}

Remote HTTP server:

{
  "mcpServers": {
    "genepattern": {
      "type": "streamable-http",
      "url": "http://localhost:3000/mcp",
      "env": {
        "GENEPATTERN_URL": "https://cloud.genepattern.org/gp",
        "GENEPATTERN_KEY": "<GP API TOKEN>"
      }
    }
  }
}

Cursor

Add via Cursor Settings → MCP Servers:

{
  "mcpServers": {
    "genepattern": {
      "command": "python",
      "args": ["server.py", "--transport", "stdio"],
      "environment": {
        "GENEPATTERN_URL": "https://cloud.genepattern.org/gp",
        "GENEPATTERN_KEY": "YOUR_TOKEN"
      }
    }
  }
}

Other MCP Clients

  • stdio: invoke server.py --transport stdio
  • HTTP/SSE: connect to http://HOST:PORT using the appropriate transport
  • Multi-user HTTP: set AUTH_HANDLER=genepattern_mcp._shared.HeaderAuthHandler and pass Authorization: Bearer <token> per request

Configuration Reference

All CLI flags have a corresponding environment variable. Environment variables are applied before CLI arguments.

Flag Env Variable Default Description
--genepattern, -g GENEPATTERN_URL https://cloud.genepattern.org/gp GenePattern server URL (include /gp)
--key, -k GENEPATTERN_KEY None Your GenePattern API Bearer token
--auth-handler, -a AUTH_HANDLER EnvAuthHandler Full Python path to an AuthHandler class (see below)
--transport, -t FASTMCP_TRANSPORT streamable-http Transport protocol: streamable-http, stdio, or sse
--port, -p FASTMCP_PORT 3000 Port to listen on (HTTP/SSE only)
--host, -H FASTMCP_HOST 0.0.0.0 Host interface to bind (HTTP/SSE only)
--local-files, -l LOCAL_FILES_ENABLED True Enable local file upload/download tools

Auth Handlers

Class Behavior
genepattern_mcp._shared.EnvAuthHandler (default) Reads GENEPATTERN_KEY from environment
genepattern_mcp._shared.HeaderAuthHandler Reads Authorization: Bearer <token> from each HTTP request
custom Subclass AuthHandler and implement get_api_key(context)

Local File Tools

When --local-files is False, the following tools are disabled:

  • upload_whole_file
  • download_job_results
  • upload_file
  • upload_job_input_from_body
  • upload_job_input_from_form
  • upload_job_output

Security Notes

  • Treat GENEPATTERN_KEY like a password — prefer environment variables over hardcoding tokens.
  • When exposing the HTTP server to a network, put it behind a reverse proxy with TLS (e.g., nginx + Let's Encrypt).
  • For multi-user deployments, use HeaderAuthHandler so each user supplies their own token per request.

Contributing & Community

We believe the best bioinformatics tools are built by the community, for the community. All skill levels welcome — whether you're a genomics researcher, an ML engineer, or just someone who wants to ask an AI to run a pathway analysis.

Ways to get involved:

  • 🐛 Found a bug? Open an issue — we triage actively.
  • 💡 Have a feature idea? Start a Discussion — we love hearing about new use cases.
  • 🔧 Want to contribute code? Fork the repo, make your changes, and open a PR. Please include tests.
  • 💬 Need help? Reach out on the GenePattern Community Forum or tag us in an issue.
# Get started with development
git clone https://github.com/genepattern/genepattern-mcp.git
cd genepattern-mcp
uv venv && source .venv/bin/activate
uv pip install -r requirements.txt
mcp dev server.py   # Explore all tools interactively

Citing This Work

If GenePattern MCP accelerates your research, please cite the underlying GenePattern platform:

Reich M, Liefeld T, Gould J, Lerner J, Tamayo P, Mesirov JP. GenePattern 2.0 Nature Genetics 38 no. 5 (2006): pp500-501 Google Scholar


License

Distributed under the BSD 3-Clause License. See LICENSE for details.

Recommended Servers

playwright-mcp

playwright-mcp

A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.

Official
Featured
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.

Official
Featured
Local
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.

Official
Featured
Local
TypeScript
VeyraX MCP

VeyraX MCP

Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.

Official
Featured
Local
graphlit-mcp-server

graphlit-mcp-server

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.

Official
Featured
TypeScript
Kagi MCP Server

Kagi MCP Server

An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

Official
Featured
Python
E2B

E2B

Using MCP to run code via e2b.

Official
Featured
Neon Database

Neon Database

MCP server for interacting with Neon Management API and databases

Official
Featured
Exa Search

Exa Search

A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.

Official
Featured
Qdrant Server

Qdrant Server

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Official
Featured