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 | 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 |
- Python 3.11+
- A GenePattern API token (see Get a Token below)
piporuv
With pip:
pip install -r requirements.txtWith uv:
uv venv && source .venv/bin/activate
uv pip install -r requirements.txtYou 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_KEYexport GENEPATTERN_KEY="YOUR_TOKEN"
python server.py --transport stdioOnce 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:
- Look up the
PreprocessDatasetmodule LSID automatically - Submit the job to GenePattern cloud
- Poll for completion and return the output file paths
mcp dev server.pyThe 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
Pull and run the official image in seconds:
docker pull genepattern/mcpRun 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/mcpUsing 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_TOKENNote:
stdiotransport is impractical inside Docker containers. Usestreamable-httpwhen containerized.
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>"
}
}
}
}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"
}
}
}
}- stdio: invoke
server.py --transport stdio - HTTP/SSE: connect to
http://HOST:PORTusing the appropriate transport - Multi-user HTTP: set
AUTH_HANDLER=genepattern_mcp._shared.HeaderAuthHandlerand passAuthorization: Bearer <token>per request
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 |
| 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) |
When --local-files is False, the following tools are disabled:
upload_whole_filedownload_job_resultsupload_fileupload_job_input_from_bodyupload_job_input_from_formupload_job_output
- Treat
GENEPATTERN_KEYlike 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
HeaderAuthHandlerso each user supplies their own token per request.
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 interactivelyIf 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
Distributed under the BSD 3-Clause License. See LICENSE for details.