home / mcp / jupyter collaboration mcp server
Provides MCP endpoints to access Jupyter Collaboration's real-time notebook and document collaboration features.
Configuration
View docs{
"mcpServers": {
"complyue-jupyter-collaboration-mcp": {
"url": "http://localhost:8888/mcp",
"headers": {
"IDENTITY_TOKEN": "your-secret-token"
}
}
}
}You can expose Jupyter Collaborationās real-time RTC features to AI agents through an MCP server. This enables agents to collaborate on notebooks and documents, see user presence and cursors, and participate in a streamed, authenticated session with resumable connections.
Connect an MCP client to the Jupyter Collaboration MCP Server to access real-time notebook and document collaboration, user awareness, and session management. Use the HTTP MCP endpoint to initialize collaboration sessions, fetch content, and stream updates. Authenticate each request with the provided token to ensure secure access.
Prerequisites you must have before installing this MCP server are Python 3.10 or higher and Jupyter Server 2.0.0 or higher.
Install the MCP server package with the following commands. Run each line separately to install the MCP server as a Jupyter server extension.
The MCP server is configured to be loaded automatically when the MCP package is installed as a Jupyter server extension. For security, authentication uses a simple token-based mechanism. Start Jupyter Lab with a token, and include this token in your MCP client requests.
{
"mcpServers": {
"jupyter_collaboration": {
"url": "http://localhost:8888/mcp",
"type": "streamable-http",
"headers": {
"Authorization": "Identity.token your-secret-token"
},
"disabled": false
}
}
}If you encounter authentication errors, verify you are using the correct token in your Authorization header. If the MCP endpoint cannot be reached, ensure the Jupyter server is running and the MCP extension is loaded. For browser-based clients, check that the server permits the origin of your client requests (CORS) or adjust the server configuration accordingly.
This MCP server exposes a set of tools for interacting with notebooks, documents, and user awareness. Use the provided HTTP endpoint to establish sessions and exchange real-time updates between AI agents and your Jupyter Collaboration environment.
List available notebooks in the collaboration environment.
Retrieve the content of a specific notebook.
Create or retrieve a collaboration session for a notebook.
Update the content of a notebook cell.
Insert a new cell into a notebook.
Delete a cell from a notebook.
Execute a specific notebook cell.
List available documents in the collaboration space.
Get the content of a document.
Create or retrieve a collaboration session for a document.
Update document content.
Insert text at a specified position in a document.
Delete text from a specified position in a document.
Retrieve the version history of a document.
Restore a document to a previous version.
Create a fork of a document.
Merge a document fork back into the original.
List users currently online in the collaboration session.
Get presence information for a user.
Set the current user's presence status.
Get cursor positions of users in a document.
Update the current user's cursor position.
Fetch recent user activities.
Broadcast user activity to other participants.
List active collaboration sessions.
Join a collaboration session.
Leave a collaboration session.