What is Scanpy MCP?
Scanpy MCP is a server designed for single-cell RNA sequencing (scRNA-Seq) analysis using natural language, built on the Scanpy framework.
How to use Scanpy MCP?
To use Scanpy MCP, install it via PyPI with the command pip install scanpy-mcp, and integrate it into AI clients or agent frameworks that support the MCP protocol.
Key features of Scanpy MCP?
- Natural language processing for reading and writing scRNA-Seq data.
- Comprehensive preprocessing capabilities including filtering, quality control, and normalization.
- Advanced tools for clustering, differential expression, and trajectory inference.
- Visualization options such as violin plots, heatmaps, and dot plots.
Use cases of Scanpy MCP?
- Performing scRNA-Seq analysis using simple natural language commands.
- Enabling developers to integrate scRNA-Seq functionalities into their applications.
- Facilitating educational demonstrations of scRNA-Seq analysis in AI environments.
FAQ from Scanpy MCP?
- Can Scanpy MCP handle all types of scRNA-Seq data?
Yes, it is designed to work with various scRNA-Seq datasets and provides flexible analysis options.
- Is there a demo available for Scanpy MCP?
Yes, a demo showcasing scRNA-Seq cell cluster analysis is available in the documentation.
- How can I install Scanpy MCP?
You can install it using
pip install scanpy-mcpor run it in a Docker container.
Scanpy MCP server
An MCP server for scRNA-Seq analysis software Scanpy 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
❓ 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 scanpy-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 scanpy-mcp
https://github.com/user-attachments/assets/93a8fcd8-aa38-4875-a147-a5eeff22a559
🏎️ Quickstart
Install
Install from PyPI
pip install scanpy-mcp
you can test it by running
scmcp run
run scnapy-server locally
Refer to the following configuration in your MCP client:
"mcpServers": {
"scanpy-mcp": {
"command": "scmcp",
"args": [
"run"
]
}
}
run scnapy-server remotely
Refer to the following configuration in your MCP client:
run it in your server
scmcp run --transport sse --port 8000
Then configure your MCP client, like this:
http://localhost:8000/sse
🤝 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!