jupyter-mcp-tools
Jupyter MCP Tools.
Decision gist · record as of 2026-08-14
Yes, if you need to expose JupyterLab commands to external MCP clients or AI agents. The package is actively maintained, has no known vulnerabilities, and carries a permissive BSD license. Install friction is low. Primary consideration: verify whether the frontend NPM package must be installed separately and whether jupyter-mcp-server is required for your use case.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires a running Jupyter Server instance and a corresponding MCP client to connect; the frontend NPM package may need separate installation.
- Low friction: pure Python wheel with only aiohttp and jupyter-server as runtime dependencies.
- Active maintenance with a release 4 days old; repository is not archived and supports Python 3.9 through 3.13.
License · maintenance · safety
permissive license (permissive) — BSD 3-Clause permissive license allows commercial and private use with minimal restrictions; you may use, modify, and distribute the software provided you retain the license notice.
last release 2026-08-10 (4 days) · last repo commit 2026-08-10 · 10 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 85,101 downloads/mo, #13,950 on PyPI
Alternatives
Verify before relying
pip install jupyter-mcp-tools
# Then enable in JupyterLab and connect via MCP client:
import aiohttp
from jupyter_mcp_tools import MCP_TOOLS
# MCP tools are automatically registered and exposed via WebSocket- Whether the extension requires a corresponding frontend NPM package (@datalayer/jupyter-mcp-tools) to be installed separately for full functionality.
- Whether jupyter-mcp-server is a required peer dependency or an optional integration point.
- Performance characteristics when exposing a large number of JupyterLab commands as MCP tools.
What it is and what it does
jupyter-mcp-tools is a JupyterLab server extension that bridges JupyterLab's command system with the Model Context Protocol (MCP), a standardized interface for AI agents and external tools. It dynamically registers all available JupyterLab commands—notebook operations, file management, kernel control, console commands, and UI toggles—as MCP tools that can be invoked remotely via WebSocket.
The extension operates in two modes: local mode executes commands directly within the JupyterLab frontend, while remote mode transmits commands via WebSocket to the backend, enabling external MCP clients and AI agents to control JupyterLab from outside the environment. It depends on aiohttp for async HTTP/WebSocket handling and jupyter-server for the backend infrastructure, and is designed to work with jupyter-mcp-server for full MCP integration.
Use it for
- Enable AI agents to open notebooks, execute cells, and manage kernel state in JupyterLab through a standardized MCP interface.
- Automate notebook workflows (append cells, run all cells, manage cell selection) triggered by external systems or chatbots.
- Provide remote file browser and document management operations (create, delete, rename, open files) to external MCP clients.
- Allow external tools to inject code into consoles, restart kernels, and manage terminal sessions without direct UI access.
- Integrate JupyterLab command execution into AI agent orchestration platforms that speak the MCP protocol.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you need to expose JupyterLab commands to external MCP clients or AI agents.
The package is actively maintained, has no known vulnerabilities, and carries a permissive BSD license. Install friction is low. Primary consideration: verify whether the frontend NPM package must be installed separately and whether jupyter-mcp-server is required for your use case.
Install
jupyter-mcp-tools on PyPI
Before you install
Low friction: pure Python wheel with only aiohttp and jupyter-server as runtime dependencies. Active maintenance with a release 4 days old; repository is not archived and supports Python 3.9 through 3.13.
Requires a running Jupyter Server instance and a corresponding MCP client to connect; the frontend NPM package may need separate installation.
License in practice
BSD 3-Clause permissive license allows commercial and private use with minimal restrictions; you may use, modify, and distribute the software provided you retain the license notice.
Quickstart
pip install jupyter-mcp-tools
# Then enable in JupyterLab and connect via MCP client:
import aiohttp
from jupyter_mcp_tools import MCP_TOOLS
# MCP tools are automatically registered and exposed via WebSocketVerify before relying
- Whether the extension requires a corresponding frontend NPM package (@datalayer/jupyter-mcp-tools) to be installed separately for full functionality.
- Whether jupyter-mcp-server is a required peer dependency or an optional integration point.
- Performance characteristics when exposing a large number of JupyterLab commands as MCP tools.
Package facts
| License | permissive license permissive |
| Python support | Supports the current Python release >=3.9 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 2 packagesaiohttpjupyter-server |
| Maintenance | Actively maintained 4 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 85,101 / month, #13,950 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Framework :: JupyterFramework :: Jupyter :: JupyterLabFramework :: Jupyter :: JupyterLab :: 4Framework :: Jupyter :: JupyterLab :: ExtensionsFramework :: Jupyter :: JupyterLab :: Extensions :: PrebuiltLicense :: OSI Approved :: BSD LicenseProgramming Language :: PythonProgramming Language :: Python :: 3Programming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.9 |
Evidence: jupyter_mcp_tools-0.1.7-py3-none-any.whl
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See also jupyter-mcp-server · jupyter-ai-tools · jupyter-ai · jupyterlab-commands-toolkit · jupyter-ai-magics · jupyter-server-mcp · jupyterlite-core · jupyter-nbmodel-client · agent-sandbox · jupyter-server-documents