- Explore MCP Servers
- decoupler-mcp
Decoupler Mcp
What is Decoupler Mcp
decoupler-mcp is an MCP server designed for analyzing biological activities, specifically for single-cell RNA sequencing (scRNA-Seq) using a natural language interface.
Use cases
Use cases include performing scRNA-Seq analysis using natural language queries, enabling agent developers to integrate decoupler’s functionalities into their applications.
How to use
To use decoupler-mcp, install it via PyPI with ‘pip install decoupler-mcp’. You can run it locally or remotely by configuring your MCP client accordingly.
Key features
Key features include an IO module for reading and writing scRNA-Seq data, pathway activity and transcription factor inference, clustering and differential expression tools, and various plotting options like violin plots and UMAP/t-SNE visualizations.
Where to use
decoupler-mcp can be used in various AI clients, plugins, or agent frameworks that support MCP, such as Cherry Studio, Cline, and Agno.
Clients Supporting MCP
The following are the main client software that supports the Model Context Protocol. Click the link to visit the official website for more information.
Overview
What is Decoupler Mcp
decoupler-mcp is an MCP server designed for analyzing biological activities, specifically for single-cell RNA sequencing (scRNA-Seq) using a natural language interface.
Use cases
Use cases include performing scRNA-Seq analysis using natural language queries, enabling agent developers to integrate decoupler’s functionalities into their applications.
How to use
To use decoupler-mcp, install it via PyPI with ‘pip install decoupler-mcp’. You can run it locally or remotely by configuring your MCP client accordingly.
Key features
Key features include an IO module for reading and writing scRNA-Seq data, pathway activity and transcription factor inference, clustering and differential expression tools, and various plotting options like violin plots and UMAP/t-SNE visualizations.
Where to use
decoupler-mcp can be used in various AI clients, plugins, or agent frameworks that support MCP, such as Cherry Studio, Cline, and Agno.
Clients Supporting MCP
The following are the main client software that supports the Model Context Protocol. Click the link to visit the official website for more information.
Content
decoupler-MCP
Natural language interface for scRNA-Seq analysis with decoupler through MCP.
🪩 What can it do?
- IO module like read and write scRNA-Seq data
- Pathway activity/Transcription factor inference
- Tool module, like clustering, differential expression etc.
- Plotting module, like violin, umap/tsne
❓ Who is this for?
- Anyone who wants to do scRNA-Seq analysis natural language!
- Agent developers who want to call decoupler’s functions for their applications
🌐 Where to use it?
You can use decoupler-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
🎬 Demo
A demo showing scRNA-Seq cell cluster analysis in a AI client Cherry Studio using natural language based on decoupler-mcp
📚 Documentation
scmcphub’s complete documentation is available at https://docs.scmcphub.org
🏎️ Quickstart
Install
Install from PyPI
pip install decoupler-mcp
you can test it by running
decoupler-mcp run
run decoupler-mcp locally
Refer to the following configuration in your MCP client:
check path
$ which decoupler /home/test/bin/decoupler-mcp
"mcpServers": { "decoupler-mcp": { "command": "/home/test/bin/decoupler-mcp", "args": [ "run" ] } }
run decoupler-server remotely
Refer to the following configuration in your MCP client:
run it in your server
decoupler-mcp run --transport shttp --port 8000
Then configure your MCP client in local AI client, like this:
"mcpServers": { "decoupler-mcp": { "url": "http://localhost:8000/mcp" } }
🤝 Contributing
If you have any questions, welcome to submit an issue, or contact me([email protected]). Contributions to the code are also welcome!
Citing
If you use decoupler-mcp in for your research, please consider citing following work:
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
Dev Tools Supporting MCP
The following are the main code editors that support the Model Context Protocol. Click the link to visit the official website for more information.










