Jupyter Notebook MCP Server
by shwetalsoni
README.md
# Jupyter Notebook MCP Server
A FastMCP server that provides tools for interacting with Jupyter notebooks. Built using the [FastMCP framework](https://github.com/jlowin/fastmcp).
## Features
- ✅ Read notebook cells with filtering
- ✅ Add new cells at any position
- ✅ Execute individual cells
- ✅ Execute entire notebooks
- ✅ Get notebook metadata and statistics
- ✅ Proper error handling and validation
- ✅ Progress reporting for long operations
- ✅ Comprehensive logging via FastMCP Context
## Integration with your MCP Client
Make sure uv is installed.
To use this server with cursor, claude desktop or any other MCP client, add the following to your mcp config file:
```json
{
"mcpServers": {
"jupyter-notebook": {
"command": "uv",
"args": [
"run",
"--with",
"fastmcp>=2.8.1",
"python",
"<absolute_path_to_jupyter_mcp_server>/main.py"
]
}
}
}
```
### Testing
Run the test client to see all functionality in action:
```bash
python test_client.py
```
## Security Notes
- Cell execution runs Python code directly via subprocess
- Only execute notebooks from trusted sources
- Consider running in a sandboxed environment for production use
- Timeout controls help prevent runaway executions
## Dependencies
- `fastmcp` - MCP server framework
## Tools
This MCP server provides the following tools for working with Jupyter notebooks:
### 📖 `read_notebook_cells`
Read cells from a Jupyter notebook with optional filtering by cell type.
**Parameters:**
- `notebook_path` (str): Path to the .ipynb file
- `cell_type` (optional str): Filter by cell type ('code', 'markdown', 'raw')
### ➕ `add_cell_to_notebook`
Add a new cell to a Jupyter notebook at a specified position.
**Parameters:**
- `notebook_path` (str): Path to the .ipynb file
- `cell_content` (str): Content of the new cell
- `cell_type` (str, default="code"): Type of cell ('code', 'markdown', 'raw')
- `position` (optional int): Position to insert cell (default: append to end)
- `metadata` (optional dict): Optional cell metadata
### ⚡ `execute_notebook_cell`
Execute a specific cell in a Jupyter notebook.
**Parameters:**
- `notebook_path` (str): Path to the .ipynb file
- `cell_index` (int): Index of the cell to execute (0-based)
- `kernel_name` (str, default="python3"): Jupyter kernel to use
- `timeout` (int, default=30): Execution timeout in seconds
### 🔄 `execute_entire_notebook`
Execute all code cells in a Jupyter notebook sequentially.
**Parameters:**
- `notebook_path` (str): Path to the .ipynb file
- `kernel_name` (str, default="python3"): Jupyter kernel to use
- `timeout_per_cell` (int, default=30): Timeout per cell in seconds
- `stop_on_error` (bool, default=True): Whether to stop execution if a cell fails
### 📊 `get_notebook_info`
Get basic information about a Jupyter notebook.
**Parameters:**
- `notebook_path` (str): Path to the .ipynb file
TDQS
A3.7/5.0
Scored across 5 tools
Disambiguation5/5
Each tool has a clearly distinct purpose: adding cells, executing entire notebook, executing a specific cell, getting notebook info, and reading cells. No overlap exists.
Naming Consistency5/5
All tool names follow a consistent verb_noun pattern using snake_case, such as add_cell_to_notebook, execute_entire_notebook, and read_notebook_cells.
Tool Count4/5
With 5 tools, the server is slightly underpopulated but still reasonable for focused notebook operations. The scope feels appropriate without being too thin.
Completeness3/5
The set covers adding, reading, and executing cells but is missing essential operations like creating or deleting notebooks and deleting cells, leaving notable gaps.
Maintenance
ActivityInactive
ResponsivenessNo issues