CellRank MCP MCP Server

$pip install cellrank-mcp
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_moduleRead and write scRNA-Seq data files.
preprocessing_modulePerform filtering, quality control, normalization, scaling, highly-variable genes selection, PCA, and Neighbors analysis.
tool_moduleExecute clustering and differential expression analysis.
plotting_moduleGenerate visualizations like violin plots, heatmaps, and dotplots.

Configuration

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

Try it

→Read my scRNA-Seq data file and perform basic quality control and normalization.
→Identify highly-variable genes and run PCA on the current dataset.
→Cluster the cells and generate a heatmap showing differential expression.
→Create a violin plot for the top marker genes in my single-cell data.

Frequently Asked Questions

What are the key features of CellRank MCP?

IO module for reading and writing scRNA-Seq data. Comprehensive preprocessing including filtering, QC, and normalization. Advanced tools for clustering and differential expression. Visualization suite for violin plots, heatmaps, and dotplots.

What can I use CellRank MCP for?

Researchers performing scRNA-Seq analysis using natural language commands. Bioinformaticians automating genomic workflows through AI agents. Developers building single-cell analysis plugins for tools like Cherry Studio or Cline. Scientists needing a unified interface for CellRank fate mapping functions.

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.

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