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Jupyter Notebook MCP Server

Jupyter Notebook MCP Server

by shwetalsoni

Jupyter Notebook MCP Server

A FastMCP server that provides tools for interacting with Jupyter notebooks. Built using the FastMCP framework.

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

Related MCP server: Jupyter MCP Server

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:

{
  "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:

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

Available Tools

5 tools
add_cell_to_notebookA
Add a new cell to a Jupyter notebook.

Args:
    notebook_path: Absolute path to the .ipynb file
    cell_content: Content of the new cell
    cell_type: Type of cell ('code', 'markdown', 'raw')
    position: Position to insert cell (default: append to end)
    metadata: Optional cell metadata

Returns:
    Status of the operation

Inputs: cell_content (required), notebook_path (required), metadata, position, +1 more.

execute_entire_notebookA
Execute all code cells in a Jupyter notebook sequentially.

Args:
    notebook_path: Absolute path to the .ipynb file
    kernel_name: Jupyter kernel to use for execution
    timeout_per_cell: Timeout per cell in seconds
    stop_on_error: Whether to stop execution if a cell fails

Returns:
    Execution summary with results for each cell

Inputs: notebook_path (required), kernel_name, stop_on_error, timeout_per_cell.

execute_notebook_cellA
Execute a specific cell in a Jupyter notebook.

Args:
    notebook_path: Absolute path to the .ipynb file
    cell_index: Index of the cell to execute (0-based)
    kernel_name: Jupyter kernel to use for execution
    timeout: Execution timeout in seconds

Returns:
    Execution result with outputs

Inputs: cell_index (required), notebook_path (required), timeout, kernel_name.

get_notebook_infoB
Get basic information about a Jupyter notebook.

Args:
    notebook_path: Absolute path to the .ipynb file

Returns:
    Notebook metadata and statistics

Inputs: notebook_path (required).

read_notebook_cellsA
Read cells from a Jupyter notebook.

Args:
    notebook_path: Absolute path to the .ipynb file
    cell_type: Optional filter by cell type ('code', 'markdown', 'raw')

Returns:
    List of cell dictionaries with metadata

Inputs: notebook_path (required), cell_type.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

Loading tool schema changelog…

    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
    ResponsivenessOutdated data

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