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MCP Jupyter Server

MCP Jupyter Server

by azharlabs
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MCP JUPYTER Server

Model Context Protocol server that exposes basic tooling for inspecting and editing Jupyter notebooks (.ipynb) from any MCP-compatible client.

Features

  • Read notebook cells with optional filtering by cell type.

  • Add, update, or delete cells while preserving notebook metadata.

  • Get quick notebook stats (cell counts, execution metadata, format version).

  • Runs over stdio so it can be wired directly into MCP clients such as Claude Desktop.

Related MCP server: mcp-server-jupyter

Requirements

  • Node.js 18 or newer.

  • Access to the .ipynb files you want to work with (local file paths).

Quick start (npx)

Run directly from the repo/package without cloning:

npx -y mcp-jupyter

Installation (local checkout)

npm install

Example MCP client entry

Point your client at the built entrypoint (adjust the path to your checkout):

 {
  "mcpServers": {
    "jupyter": {
      "command": "npx",
      "args": [
        "-y",
        "mcp-jupyter"
      ],
      "cmd": ""
    }
  },
  "$version": 2
}

Available tools

Position-Based Operations

  • list_cells - List all cells with indices and type information

  • get_cell_source - Get source code of specific cells by index

  • edit_cell_source - Edit cell content by index

  • insert_cell - Insert new cells at specific positions

  • delete_cell - Delete cells by index with automatic reindexing

Enhanced Operations

  • move_cell - Move cells between positions

  • convert_cell_type - Convert between code/markdown/raw cells

  • bulk_edit_cells - Perform multiple operations in a single call

Available Tools

13 tools
add_cellC

Add a new cell to the notebook

Inputs: notebook_path (required), source, cell_type, position.

bulk_edit_cellsC

Perform bulk operations on multiple cells

Inputs: notebook_path (required), operations (required).

convert_cell_typeC

Convert a cell from one type to another

Inputs: notebook_path (required), cell_index (required), new_type (required).

delete_cellC

Delete a cell by index

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

edit_cellC

Edit the source code of a specific cell by ID or index

Inputs: notebook_path (required), cell_id (required), new_source (required).

edit_cell_sourceC

Edit the source code of a specific cell by index

Inputs: notebook_path (required), cell_index (required), new_source (required).

execute_cellC

Execute a specific cell in the notebook using a Jupyter kernel

Inputs: notebook_path (required), cell_id (required).

get_cell_sourceC

Get the source code of a specific cell by index

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

insert_cellC

Insert a new cell at a specific position

Inputs: notebook_path (required), position (required), cell_type, source.

list_cellsA

List all cells in a Jupyter notebook with their indices and types

Inputs: notebook_path (required).

move_cellC

Move a cell from one position to another

Inputs: notebook_path (required), from_index (required), to_index (required).

read_notebook_with_outputsC

Read a Jupyter notebook including cell outputs

Inputs: notebook_path (required).

trigger_vscode_reloadC

Trigger VS Code to reload the notebook file

Inputs: notebook_path (required).

Tool Schema Changelog

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

Loading tool schema changelog…

    Deploy Server
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    TDQS

    B3.2/5.0

    Scored across 13 tools

    Disambiguation3/5

    Most tools have distinct purposes for cell operations, but there is notable overlap between 'edit_cell' and 'edit_cell_source' which both edit cell source code, and between 'add_cell' and 'insert_cell' which both add cells. This could cause confusion for an agent trying to select the right tool.

    Naming Consistency4/5

    Tool names follow a consistent verb_noun pattern (e.g., add_cell, delete_cell, execute_cell) with clear actions and targets. The only deviation is 'read_notebook_with_outputs' which is longer but still follows the pattern, and 'trigger_vscode_reload' which uses a verb_noun_noun structure but remains readable.

    Tool Count5/5

    With 13 tools, this server is well-scoped for managing Jupyter notebooks, covering a comprehensive set of operations like adding, editing, executing, and listing cells. Each tool appears to serve a specific function without unnecessary bloat.

    Completeness4/5

    The toolset provides strong coverage for cell-level operations (CRUD, execution, type conversion) and notebook reading, but lacks tools for higher-level notebook management such as saving, creating new notebooks, or kernel control. Minor gaps exist, but agents can likely work around them.

    Maintenance

    ActivityInactive
    ResponsivenessNo recent community issues

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