Biomarker MCP
Natural language interface for celltype marker query through MCP.
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biomarker-MCP
Natural language interface for celltype marker query through MCP.
πͺ© What can it do?
- query celltype marker from CellMarker database by natural language
- will add more database
β Who is this for?
- Anyone who wants to do query celltype marker with natural language!
- Agent developers who want to query cell markers for their applications
π Where to use it?
You can use biomarker-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
π¬ Demo
A demo showing query celltype markers in a AI client Cherry Studio using natural language based on biomarker-mcp
https://github.com/user-attachments/assets/71268f6f-c74d-4142-ad7a-893b411d748a
π Documentation
scmcphub's complete documentation is available at https://docs.scmcphub.org
ποΈ Quickstart
Install
Install from PyPI
pip install biomarker-mcp
you can test it by running
biomarker-mcp run
run biomarker-mcp locally
Refer to the following configuration in your MCP client:
check path
$ which biomarker
/home/test/bin/biomarker-mcp
"mcpServers": {
"biomarker-mcp": {
"command": "/home/test/bin/biomarker-mcp",
"args": [
"run"
]
}
}
run biomarker-server remotely
Refer to the following configuration in your MCP client:
run it in your server
biomarker-mcp run --transport shttp --port 8000
Then configure your MCP client in local AI client, like this:
"mcpServers": {
"biomarker-mcp": {
"url": "http://localhost:8000/mcp"
}
}
π€ 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 biomarker-mcp in for your research, please consider citing following work:
Congxue Hu, Tengyue Li, Yingqi Xu, Xinxin Zhang, Feng Li, Jing Bai, Jing Chen, Wenqi Jiang, Kaiyue Yang, Qi Ou, Xia Li, Peng Wang, Yunpeng Zhang, CellMarker 2.0: an updated database of manually curated cell markers in human/mouse and web tools based on scRNA-seq data, Nucleic Acids Research, Volume 51, Issue D1, 6 January 2023, Pages D870βD876, https://doi.org/10.1093/nar/gkac947
