Intelli builds chatbots and agents from user-defined intents and model choices.
Open source
24 alternativesJupyter AI
Jupyter AI adds an AI chat interface and agent capabilities to JupyterLab notebooks.
About Jupyter AI
Jupyter AI is an open source extension that connects AI agents to computational notebooks in JupyterLab. It provides a chat interface that works with installed agents such as Claude, Codex, GitHub Copilot, Gemini, Goose, Kiro, Mistral Vibe, and OpenCode through the Agent Client Protocol, with agents detected when their dependencies are installed.
Agents can read and write files, run terminal commands, and interact with notebooks through a built-in Jupyter MCP server, with approval prompts before file writes or command execution. It supports multiple concurrent chats, drag-and-drop of files or notebook cells as context, real-time collaboration with other users on the same server, and custom MCP servers and AI personas via the entry points API.
Key features
- Chat interface in JupyterLab for AI agents via ACP
- Support for Claude, Copilot, Gemini, Goose, Kiro and others
- Agents can read and write files and run terminal commands
- Notebook interaction through built-in Jupyter MCP server
- Approval prompts before file writes or command execution
- Multiple concurrent chats with file or cell context
Best for: JupyterLab users who want to use AI agents with notebooks, files, and terminal commands.
Good for
- Open source under BSD-3-Clause license
- Works with multiple agents via ACP and MCP open standards
- Includes approval prompts for file writes and command execution
Jupyter AI at a glance
- Type
- Open-source project
- Pricing
- Not confirmed. Check the site
- Open source
- Yes · Source code
- Language
- English
- Last checked
- Oct 5, 2026 · Online when checked
- Listed
- Oct 5, 2026
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Jupyter AI FAQ
How do agents become available in Jupyter AI?
Agents are automatically detected when their dependencies are installed alongside Jupyter AI.
What can agents do in JupyterLab?
Agents can read and write files, run terminal commands, and interact with notebooks through the built-in Jupyter MCP server.
Can I extend what agents can access?
Custom MCP servers can be added to provide domain-specific tools, resources, and prompts.
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