Skip to main content
Pre-release

This release is a pre-release and may not be stable for production use.

Jupyter Claude Plugin

A JupyterLab extension enabling collaborative development between users and Claude. Chat about your notebook, generate cells from prompts, explain and document existing code, and fix errors — all within JupyterLab.

Status: early development, scaffold phase complete. See docs/PLAN.md for the implementation plan and docs/DECISIONS.md for the decision log.

Jupyter Claude Plugin

Features (v1)

  • Chat about the notebook — ask Claude to analyze, summarize, or answer questions about your entire notebook
  • Generate a cell — describe what you want; choose cell type (code/markdown/raw); Claude generates and inserts it
  • Explain a cell — Claude documents an existing cell with a markdown explanation
  • Fix last error — Claude sees the error from your last cell run and offers a corrected version
  • Runtime tier selector — switch between opus/sonnet/haiku in the chat panel for quality/speed tradeoffs (Bedrock only)
  • MCP server management — enable/disable individual MCP servers from ~/.claude.json per session via dialog command (defaults to Jupyter only for faster startup)
  • Notebook toolbar buttons — all five commands as icons in toolbar: Open Chat, Generate cell, Explain cell, Fix last error, and MCP server selector
  • Visual feedback — animated "Claude is thinking…" spinner while processing; disabled tier selector during requests

Requirements

  • JupyterLab >= 4.0.0
  • Node >= 20
  • Python >= 3.10 (this project targets 3.13)
  • uv package manager (via Homebrew: brew install uv)

Install (from PyPI, recommended)

pip install --pre jupyter-claude-plugin

--pre is required for alpha releases (currently 0.1.0a1). Runtime dependencies (claude-agent-sdk, jupyter-mcp-server, jupyter-collaboration) are pulled in automatically. See docs/USER_GUIDE.md for backend configuration and usage.

Development install (from source)

cd /path/to/Jupyter-Claude_Plugin
uv venv
source .venv/bin/activate

jlpm install
uv pip install -e ".[dev,test]"
jlpm build
jupyter labextension develop . --overwrite
jupyter server extension enable jupyter_claude

jupyter lab

Global MCP servers (user scope, one-time)

claude mcp add --scope user filesystem -- npx -y @modelcontextprotocol/server-filesystem $HOME
claude mcp add --scope user memory -- npx -y @modelcontextprotocol/server-memory
claude mcp add --scope user sequential-thinking -- npx -y @modelcontextprotocol/server-sequential-thinking
claude mcp add --scope user fetch -- uvx mcp-server-fetch
claude mcp add --scope user git -- uvx mcp-server-git
claude mcp add --scope user jupyter --transport http http://localhost:8888/mcp

Backend

The extension supports two Claude backends. Pick one in the JupyterLab Settings Editor (or via jupyter_server_config.py) — everything else is derived from that choice.

Anthropic direct

Set ANTHROPIC_API_KEY in the environment before launching Jupyter. The extension will use the model trait (default claude-opus-4-8).

AWS Bedrock via shared SSO

Configuration lives in the extension traits (not shell env — the extension writes the right vars into the Claude Agent SDK subprocess itself):

  • backend = "bedrock"
  • aws_region = "us-east-1" (or your region)
  • aws_profile = "<your profile>" — a named profile from ~/.aws/config (enables shared AWS SSO; profile and region are forwarded to the SDK subprocess)
  • default_opus_model, default_sonnet_model, default_haiku_model — inference-profile model IDs (defaults: us.anthropic.claude-opus-4-7, us.anthropic.claude-sonnet-4-6, us.anthropic.claude-haiku-4-5-20251001-v1:0)

Refresh your SSO session and start Jupyter with aws-vault so the subprocess inherits temporary STS credentials without leaking them to disk:

aws sso login --profile <your profile>              # once per session
aws-vault exec <your profile> -- jupyter lab

If you prefer not to use aws-vault, AWS_PROFILE=<name> AWS_REGION=<region> jupyter lab also works — the extension forwards those to the SDK.

See docs/PLAN.md for design details.

Architecture

JupyterLab (browser)
  └─ Frontend extension (TS/React)
       ├─ Right-side chat panel
       ├─ Cell toolbar buttons
       └─ Context-menu items
                          ↓ WebSocket
                  Server extension (Python)
                    └─ ClaudeSDKClient
                         ├─ Anthropic API | AWS Bedrock
                         └─ Jupyter MCP server (same process)

Claude reads/writes/executes cells via MCP tools; the extension provides no custom cell tools.

Troubleshoot

If the frontend extension is not working, check that the server extension is enabled:

jupyter server extension list

If the server extension is installed and enabled but the frontend is not showing up, check that the frontend extension is installed:

jupyter labextension list

Documentation

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

jupyter_claude_plugin-0.1.0a3.tar.gz (370.0 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

jupyter_claude_plugin-0.1.0a3-py3-none-any.whl (115.9 kB view details)

Uploaded Python 3

File details

Details for the file jupyter_claude_plugin-0.1.0a3.tar.gz.

File metadata

  • Download URL: jupyter_claude_plugin-0.1.0a3.tar.gz
  • Upload date:
  • Size: 370.0 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/7.0.0 CPython/3.13.14

File hashes

Hashes for jupyter_claude_plugin-0.1.0a3.tar.gz
Algorithm Hash digest
SHA256 72ed88ba160028268b1350d135179d994230c452e84532501e11b174aa9660f4
MD5 aeb43d1ab166f5a0d25d0bcabe96cd41
BLAKE2b-256 17eeb61aacfc93cf02afb9304916f0e2bb741a2f4c5d03e417de7af5776ef1fa

See more details on using hashes here.

File details

Details for the file jupyter_claude_plugin-0.1.0a3-py3-none-any.whl.

File metadata

File hashes

Hashes for jupyter_claude_plugin-0.1.0a3-py3-none-any.whl
Algorithm Hash digest
SHA256 7c6383e2fa5d353fefdd9791e9a1fc62ec3508b2f3295320959488c0d21a85d9
MD5 d5c6d580b5e31a1a8080762f475569a7
BLAKE2b-256 35adfc3eb4196b9e4539fe6bf51081430dec50e496118d2a2a85a8acd21d43e5

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page