Install
$ agentstack add mcp-scmcphub-scanpy-mcp ✓ scanned · ✓ verified — works with Claude Code, Cursor, and more.
Security review
✓ PassedNo issues found. Passed automated security review. · v0.1.0 How review works →
- ✓ Prompt-injection patterns
- ✓ Secret / credential exfiltration
- ✓ Dangerous shell & filesystem operations
- ✓ Untrusted network calls
- ✓ Known-malicious package signatures
What it can access
- ✓ Network access No
- ✓ Filesystem access No
- ✓ Shell / process execution No
- ✓ Environment & secrets No
- ✓ Dynamic code execution No
From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.
About
Scanpy-MCP
Natural language interface for scRNA-Seq analysis with Scanpy through MCP.
🪩 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 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
📚 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 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
scanpy-mcp run
run scnapy-mcp locally
Refer to the following configuration in your MCP client:
check path
$ which scanpy
/home/test/bin/scanpy-mcp
"mcpServers": {
"scanpy-mcp": {
"command": "//home/test/bin/scanpy-mcp",
"args": [
"run"
]
}
}
run scnapy-mcp remotely
Refer to the following configuration in your MCP client:
run it in your server
scanpy-mcp run --transport shttp --port 8000
Then configure your MCP client in local AI client, like this:
"mcpServers": {
"scanpy-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 scanpy-mcp in for your research, please consider citing following work: > 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
Source & license
This open-source MCP server is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: scmcphub
- Source: scmcphub/scanpy-mcp
- License: BSD-3-Clause
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.