Agentic backend coder - A Jupyter notebook manager with MCP (Model Context Protocol) integration for AI-assisted code execution and bioinformatics workflows.
Supports multiple Jupyter kernels (Python, R, etc.) for parallel notebook management.
- Jupyter Notebook Management: Create, switch between, and manage multiple Jupyter notebooks
- Multi-kernel Support: Manage and run code in multiple Jupyter kernels (e.g., Python, R) simultaneously
- Code Execution: Execute single-step or multi-step code in Jupyter kernels
- Variable Backup: Safely backup variables before code execution to prevent data loss
- API Documentation: Query function and API documentation directly from the kernel
- Output Handling: Capture and display execution results, errors, and generated figures
- Bioinformatics Integration: Designed for bioinformatics workflows with support for common libraries like scanpy, pandas, numpy, etc.
- Bioinformaticians who want AI assistance in their Jupyter workflows
- AI developers building agents that need to execute code in Jupyter environments
- Researchers who want to integrate AI tools with their computational notebooks
- Anyone who wants to use natural language to control Jupyter notebook execution
You can use abcoder in most AI clients, plugins, or agent frameworks that support the MCP:
- AI clients: Cherry Studio, Claude Desktop, etc.
- Plugins: Cline, etc.
- Agent frameworks: Agno, etc.
A demo showing AI-assisted bioinformatics analysis in a Jupyter notebook using natural language commands through abcoder.
Click the image above to watch the demo video
For complete documentation, visit: https://github.com/huang-sh/abcoder
Install from PyPI:
pip install abcoderTest the installation:
abcoder runFirst, check the installation path:
which abcoder
# Example output: /home/user/bin/abcoderConfigure your MCP client:
{
"mcpServers": {
"abcoder": {
"command": "/home/user/bin/abcoder",
"args": ["run"]
}
}
}Start the server on your remote machine:
abcoder run --transport shttp --port 8000Configure your local MCP client:
{
"mcpServers": {
"abcoder": {
"url": "http://localhost:8000/mcp"
}
}
}create_notebook: Create a new Jupyter notebook with specified ID and pathswitch_active_notebook: Switch between different notebooks
single_step_execute: Execute a single code blockmulti_step_execute: Execute multiple code steps with cell additionquery_api_doc: Query function documentation from the kernel
- Variable Backup: Automatically backup variables before execution
- Error Handling: Comprehensive error capture and reporting
- Output Display: Support for text, images, and other display data
- Kernel Management: Automatic kernel lifecycle management
If you have any questions, welcome to submit an issue, or contact me(hsh-me@outlook.com). Contributions to the code are also welcome!