CellRank MCP Server

Local setup required. This server has to be cloned and prepared on your machine before you register it in Claude Code.
1

Set the server up locally

Run this once to clone and prepare the server before adding it to Claude Code.

Run in terminal
pip install cellrank-mcp
2

Register it in Claude Code

After the local setup is done, run this command to point Claude Code at the built server.

Run in terminal
claude mcp add cellrank-mcp -- node "<FULL_PATH_TO_CELLRANK_MCP>/dist/index.js"

Replace <FULL_PATH_TO_CELLRANK_MCP>/dist/index.js with the actual folder you prepared in step 1.

README.md

Natural language interface for scRNA-Seq analysis with cellrank through MCP.

cellrank-MCP

Natural language interface for scRNA-Seq analysis with cellrank through MCP.

đŸĒŠ What can it do?

  • IO module like read and write scRNA-Seq data
  • Preprocessing module,like filtering, quality control, normalization, scaling, highly-variable genes, PCA, Neighbors,...
  • Tool module, like clustering, differential expression etc.
  • Plotting module, like violin, heatmap, dotplot

❓ Who is this for?

  • Anyone who wants to do scRNA-Seq analysis natural language!
  • Agent developers who want to call cellrank's functions for their applications

🌐 Where to use it?

You can use cellrank-mcp in most AI clients, plugins, or agent frameworks that support the MCP:

  • AI clients, like Cherry Studio
  • Plugins, like Cline
  • Agent frameworks, like Agno

📚 Documentation

scmcphub's complete documentation is available at https://docs.scmcphub.org

đŸŽŦ Demo

A demo showing scRNA-Seq cell cluster analysis in a AI client Cherry Studio using natural language based on cellrank-mcp

đŸŽī¸ Quickstart

Install

Install from PyPI

pip install cellrank-mcp

you can test it by running

cellrank-mcp run
run cellrank-mcp locally

Refer to the following configuration in your MCP client:

check path

$ which cellrank 
/home/test/bin/cellrank-mcp
"mcpServers": {
  "cellrank-mcp": {
    "command": "/home/test/bin/cellrank-mcp",
    "args": [
      "run"
    ]
  }
}
run cellrank-server remotely

Refer to the following configuration in your MCP client:

run it in your server

cellrank-mcp run --transport shttp --port 8000

Then configure your MCP client in local AI client, like this:


"mcpServers": {
  "cellrank-mcp": {
    "url": "http://localhost:8000/mcp"
  }
}

🤝 Contributing

If you have any questions, welcome to submit an issue, or contact me(hsh-me@outlook.com). Contributions to the code are also welcome!

Citing

If you use cellRank-mcp in for your research, please consider citing following work:

Weiler, P., Lange, M., Klein, M. et al. CellRank 2: unified fate mapping in multiview single-cell data. Nat Methods 21, 1196–1205 (2024). https://doi.org/10.1038/s41592-024-02303-9

Tools (4)

io_moduleHandles reading and writing of scRNA-Seq data files.
preprocessing_modulePerforms data filtering, quality control, normalization, scaling, and PCA.
tool_moduleExecutes analytical tasks like clustering and differential expression analysis.
plotting_moduleGenerates visualizations including violin plots, heatmaps, and dotplots.

Configuration

claude_desktop_config.json
{"mcpServers": {"cellrank-mcp": {"command": "cellrank-mcp", "args": ["run"]}}}

Try it

→Load the scRNA-Seq dataset from the provided file path.
→Perform quality control and normalization on the loaded dataset.
→Run clustering analysis on the preprocessed data.
→Generate a heatmap visualization of the top highly-variable genes.
→Calculate differential expression between the identified cell clusters.

Frequently Asked Questions

What are the key features of CellRank MCP?

IO module for reading and writing scRNA-Seq data. Preprocessing capabilities including filtering, QC, and normalization. Clustering and differential expression analysis tools. Visualization module for generating violin plots, heatmaps, and dotplots.

What can I use CellRank MCP for?

Performing automated scRNA-Seq preprocessing workflows via natural language. Integrating CellRank analysis capabilities into AI-powered agent frameworks. Rapidly generating genomic data visualizations for research reports. Streamlining differential expression analysis for single-cell datasets.

How do I install CellRank MCP?

Install CellRank MCP by running: pip install cellrank-mcp

What MCP clients work with CellRank MCP?

CellRank MCP works with any MCP-compatible client including Claude Desktop, Claude Code, Cursor, and other editors with MCP support.

Turn this server into reusable context

Keep CellRank MCP docs, env vars, and workflow notes in Conare so your agent carries them across sessions.

Need the old visual installer? Open Conare IDE.
Open Conare