Biomarker

Natural language interface for celltype marker query through MCP.

🪩 What can it do?

• query celltype marker from CellMarker database by natural language
• will add more database

❓ 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

🌐 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

🎬 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

📚 Documentation

scmcphub's complete documentation is available at https://docs.scmcphub.org

🏎️ 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"
  }
}

🤝 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 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 D870–D876, https://doi.org/10.1093/nar/gkac947