Better Native Jupyter Notebook MCP Server

A VS Code / Cursor extension that exposes Jupyter notebook manipulation via MCP (Model Context Protocol): read/edit/run cells and capture outputs. Works with Claude Code, Cursor Agent, Windsurf, and any MCP-compatible AI assistant.
Install: VS Code Marketplace · Open VSX · GitHub
[!IMPORTANT]
This project is still pre-alpha so it's very rough on the edge. Working in multiple windows is unstable.
Why connect to VS Code Runtime API?
There are currently two main architectures to give AI agents access to Jupyter notebooks. This project was heavily inspired by both - kudos to these teams for pioneering the space:
These servers read/write .ipynb files directly using libraries like nbformat.
Pros: No server dependencies, works out-of-the-box
Cons:
- Cannot execute code - agents can only edit cells, user must run them manually
- UI sync issues - VS Code may show stale content until you revert/reopen
- The
.ipynb JSON format is verbose (~3x more tokens than raw code)
- Race conditions if you edit while agent writes
Architecture 2: Jupyter Server API (e.g., jupyter-mcp-server)
These servers connect to Jupyter's REST API and can execute code through the kernel.
Pros: Can execute code, best choice for standalone remote JupyterLab/JupyterHub deployments
Cons:
- Requires running JupyterLab separately (
jupyter lab --port 8888)
- Auth setup: tokens, URLs, environment variables
- You end up running two UIs: one for notebook and another for AI
- If you open the notebook in VS Code you create another source of truth (Jupyter server state vs your editor)
Architecture 3: VS Code / Cursor Runtime API (this extension)
We're introducing a third architecture - hooking directly into Cursor/VS Code's Notebook API, the same API the editor uses internally.
Pros:
- Zero config - just install, server starts automatically
- Faster reads (direct memory access, no serialization)
- Executes code in your existing kernel (the one VS Code already manages)
- Changes appear instantly in the editor with full undo/redo support
- Single source of truth: what you see is what the agent sees
- Works with remote kernels - if VS Code connects to a remote Jupyter server, so does the agent
Cons:
- Only works inside VS Code / Cursor (won't help if you use JupyterLab web UI)
When to use what
| Use case |
Recommended |
| VS Code / Cursor + AI coding |
This extension |
| Remote VS Code / Cursor (tunnels, containers, SSH) |
This extension |
| Standalone JupyterLab/JupyterHub server |
Datalayer |
| Just edit cells, no execution needed |
File-based |
Features
- Execute code in the active kernel and retrieve outputs
- Full cell manipulation - insert, edit, delete, move cells
- Read cell contents and outputs including images (base64)
- Search and navigate - find text, get notebook outline
- Bulk operations - add multiple cells, clear all outputs
Navigation & Reading
| Tool |
Description |
notebook_list_open |
List all open notebooks with URIs and cell counts |
notebook_list_cells |
List cells with type, language, preview, execution state |
notebook_get_cell_content |
Get full source code of a cell |
notebook_get_cell_output |
Get cell outputs (text, errors, images as base64) |
notebook_get_outline |
Get notebook structure (headings, functions, classes) |
notebook_search |
Search all cells for a keyword with context |
notebook_get_kernel_info |
Get kernel name, language, and state |
Cell Manipulation
| Tool |
Description |
notebook_insert_cell |
Insert a code or markdown cell at any position |
notebook_edit_cell |
Replace the content of an existing cell |
notebook_delete_cell |
Delete a cell by index |
notebook_move_cell |
Move a cell to a different position |
notebook_bulk_add_cells |
Add multiple cells in a single operation |
Execution & Outputs
To execute ad-hoc code, use notebook_insert_cell with execute: true. To execute an existing cell, use notebook_run_cell.
Any open notebook can be targeted with notebook_uri, on screen or not. A run in a notebook on
screen happens in the cell, with its output under it. A run in a notebook that is not on screen
goes to that notebook's kernel: the output comes back to the agent but is not shown under the
cell, and your view never moves. notebook_show brings a notebook into view first; the
notebook-mcp.showNotebookToRun setting does that automatically for every run.
| Tool |
Description |
notebook_save |
Save a notebook to disk through VS Code (no conflict with the open editor) |
notebook_show |
Bring an open notebook into view, optionally at a cell (keyboard focus stays put) |
notebook_run_cell |
Execute an existing code cell by index and return outputs (timeout_seconds, default 60; past it the result says "running", and calling it again keeps waiting) |
notebook_run_cells |
Run a range of cells in order (default all), stopping at the first failure |
notebook_interrupt_kernel |
Stop the running cell (variables are kept) |
notebook_restart_kernel |
Restart the kernel; VS Code may ask you to confirm |
notebook_clear_outputs |
Clear outputs of a specific cell |
notebook_clear_all_outputs |
Clear outputs from all cells |
Tool Parameters
All tools support response_format parameter ("markdown" or "json").
notebook_insert_cell
{
"content": "print('hello')",
"type": "code",
"index": 0,
"language": "python",
"execute": false
}
notebook_edit_cell
{
"index": 0,
"content": "# New content"
}
notebook_search
{
"query": "import pandas",
"case_sensitive": false,
"context_lines": 1
}
notebook_move_cell
{
"from_index": 5,
"to_index": 0
}
notebook_bulk_add_cells
{
"cells": [
{"content": "# Header", "type": "markdown"},
{"content": "x = 1", "type": "code", "language": "python"}
],
"index": 0
}
notebook_run_cell
{
"index": 0
}
Setup
This fork is installed from its own build, never the Marketplace (its extension ID,
Submersible.better-notebook-mcp-server, is not published, so VS Code never auto-updates it):
npm ci --ignore-scripts
npm run package
code --install-extension better-notebook-mcp-server-*.vsix
On first start the extension writes a random token to ~/.config/notebook-mcp/token (mode 0600).
Every request must send it as Authorization: Bearer <token>; requests carrying an Origin
header (any browser page) or a non-loopback Host (DNS rebinding) are refused. Register it with
Claude Code so the token is read from that file on each connect, never copied into config:
claude mcp add-json --scope user notebook \
'{"type":"http","url":"http://127.0.0.1:49777/mcp","headersHelper":"printf %s \"{\\\"Authorization\\\":\\\"Bearer $(tr -d \"\\n\" < \"$HOME/.config/notebook-mcp/token\")\\\"}\""}'
[!ATTENTION]
The server starts automatically when VS Code / Cursor opens. Look for the 🪐 :49777 indicator in the status bar.
Configuration
| Setting |
Default |
Description |
notebook-mcp.port |
49777 |
Port number for the MCP server |
notebook-mcp.showNotebookToRun |
false |
Bring a notebook that is not on screen into view to run a cell in it, instead of running in its kernel |
Tested with a 471-cell notebook (~2.8MB, 1MB outputs):
| Operation |
Time |
| List/read cells |
<1ms |
| Search all cells |
<1ms |
| Generate outline |
~1ms |
| Insert/edit cell |
~7ms |
[!NOTE]
Read operations are sub-millisecond because they access in-memory data structures directly. Write operations (~7ms) go through VS Code's edit pipeline for undo/redo support.
Requirements
Architecture
┌─────────────────────────────────────────────────────────────────────────┐
│ VS Code / Cursor │
│ │
│ ┌───────────────────────────────────────────────────────────────────┐ │
│ │ Jupyter Extension │ │
│ │ │ │
│ │ Notebook Document ◄───► Kernel (Python) ───► Outputs │ │
│ │ ▲ │ │
│ └────────────────────────────────────┼──────────────────────────────┘ │
│ │ │
│ ┌────────────────────────────────────┼──────────────────────────────┐ │
│ │ Notebook MCP Server Extension │ │
│ │ │ │ │
│ │ ┌────────────────────────────────┴───────────────────────────┐ │ │
│ │ │ HTTP Server (:49777) │ │ │
│ │ │ │ │ │
│ │ │ execute_code insert_cell list_cells get_output ... │ │ │
│ │ └────────────────────────────────────────────────────────────┘ │ │
│ └───────────────────────────────────────────────────────────────────┘ │
└─────────────────────────────────────────────────────────────────────────┘
│
│ HTTP (MCP Protocol)
▼
┌───────────────────────────────┐
│ AI Agent │
│ (Claude Code, Cursor, etc) │
└───────────────────────────────┘
How It Works
- Extension embeds an HTTP-based MCP server (port 49777)
- AI agent (Claude Code, Cursor Agent, etc.) sends tool calls via MCP protocol
- Server uses VS Code / Cursor APIs to manipulate the active notebook
- Changes appear instantly in the editor
- Outputs are captured and returned to the agent
This enables true interactive notebook sessions with AI agents in VS Code and Cursor.