scmcp

SCMCP

An MCP server for scRNA-Seq analysis with natural language!

🪩 What can it do?

• IO module like read and write scRNA-Seq data with natural language
• 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
• cell-cell communication analysis
• Pseudotime analysis
• enrichment analysis

❓ Who is this for?

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

🌐 Where to use it?

You can use scmcp 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

🎬 Demo

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

https://github.com/user-attachments/assets/93a8fcd8-aa38-4875-a147-a5eeff22a559

🏎️ Quickstart

Install

Install from PyPI

pip install scmcp

you can test it by running

scmcp run

run scnapy-mcp locally

Refer to the following configuration in your MCP client:

check path

$ which scmcp 
/home/test/bin/scmcp

it has many tools , so it couldn't work if you model context is not large...More time, I recommend it is backend mcp server for scanpy-mcp, liana-mcp,cellrank-mcp, so they can use shared Anndata object.

"mcpServers": {
  "scmcp": {
    "command": "/home/test/bin/scmcp",
    "args": [
      "run"
    ]
  }
}

run scmcp remotely

Refer to the following configuration in your MCP client:

run it in your server

scmcp run --transport shttp --port 8000

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

"mcpServers": {
  "scmcp": {
    "url": "http://localhost:8000/mcp"
  }
}

Intelligent Tool Selection (Experimental)

SCMCP implements an intelligent tool selection system to optimize performance and reduce token usage.

How it Works

The intelligent tool selection system operates in two phases:

1. Search_tool: First identifies the most relevant tools for your analysis
2. run_tool: Then runs only the selected tools, reducing token consumption

Usage

1. Ensure you have the latest version of scmcp-shared installed:

pip install --upgrade scmcp-shared

2. Start the server with intelligent tool selection enabled:

export API_KEY=sk-***
export BASE_URL="https://api.openai.com/v1"
export MODEL="gpt-4o"
scmcp run --transport shttp --port 8000 --tool-mode auto

3. Configure your MCP client to connect to the server:

{
  "mcpServers": {
    "scmcp": {
      "url": "http://localhost:8000/mcp"
    }
  }
}

🤝 Contributing

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

Citing

If you use scmcp in for your research, please consider citing following works:

Wolf, F., Angerer, P. & Theis, F. SCANPY: large-scale single-cell gene expression data analysis. Genome Biol 19, 15 (2018). https://doi.org/10.1186/s13059-017-1382-0

Dimitrov D., Schäfer P.S.L, Farr E., Rodriguez Mier P., Lobentanzer S., Badia-i-Mompel P., Dugourd A., Tanevski J., Ramirez Flores R.O. and Saez-Rodriguez J. LIANA+ provides an all-in-one framework for cell–cell communication inference. Nat Cell Biol (2024). https://doi.org/10.1038/s41556-024-01469-w

Badia-i-Mompel P., Vélez Santiago J., Braunger J., Geiss C., Dimitrov D., Müller-Dott S., Taus P., Dugourd A., Holland C.H., Ramirez Flores R.O. and Saez-Rodriguez J. 2022. decoupleR: ensemble of computational methods to infer biological activities from omics data. Bioinformatics Advances. https://doi.org/10.1093/bioadv/vbac016

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