Does Notebook Intelligence require JupyterLab?
Yes, Notebook Intelligence requires JupyterLab version 4.0.0 or higher.
@notebook-intelligence
Basic information
No overview available yet
No standard config provided
This server doesn't expose a parseable MCP config block in its README. See the repository for install instructions.
RepositoryTool list not available yet
This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.
We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.
Notebook Intelligence (NBI) is an AI coding assistant and extensible AI framework for JupyterLab. It works with GitHub Copilot, any LLM provider, or local models via Ollama, boosting JupyterLab user productivity with in‑line code generation, auto‑complete, and a chat interface.
Install the extension with pip install notebook-intelligence (requires JupyterLab ≥ 4.0.0) and restart JupyterLab. Configure the LLM provider and model through the Settings dialog, via the command palette, or by editing the config file at ~/.jupyter/nbi-config.json.
Yes, Notebook Intelligence requires JupyterLab version 4.0.0 or higher.
Use the Notebook Intelligence Settings dialog (accessible from JupyterLab’s Settings menu or the `/settings` chat command) or manually edit `~/.jupyter/nbi-config.json`. API keys for custom providers are stored in that config file.
It supports both Standard Input/Output (stdio) and Server‑Sent Events (SSE) transports. MCP support is currently limited to server tools.
Notebook Intelligence uses the system keyring via the `keyring` package. To remember a token, launch JupyterLab with `--NotebookIntelligence.github_access_token=remember`; to forget it, use `forget`.
Yes. In the `mcp.tools` configuration of `nbi-config.json`, use the `"alwaysAllow"` key with a list of tool names to auto‑approve those specific tools.

Sooveryn gives Claude Code a team of AI personas that remembers your project. Soov, the partner and team lead, keeps your decisions and how you work in a lasting memory, and finds them again by words and by meaning, from
Local MCP server and CLI that keeps a Git-versioned, model-written index of a codebase and its database schema, so coding agents start each task with the whole system in view.

Open-source Python SDK & MCP interface for Priostack Agent Context Network (ACN). Zero-setup, autonomous memory orchestration for AI agents.
Project context your AI can query through MCP — with source evidence.

Orcha is a unified context layer for AI tools and agents. It stores and indexes and exposes organizational, team, or individual knowledge. Files, structured databases, and connected sources live in one workspace, and age
Comments