Inspizzz/jetbrains-datalore-mcp

Overview

This is a Model Context Protocol (MCP) server that wraps the Jetbrains Datalore API. It allows AI agents to run notebooks (including interactive runs), fetch run data, and retrieve files from cloud-based Datalore instances. The server acts as a bridge between MCP-compatible clients and the Datalore platform.

Best for

Best for
Data scientists and MLOps engineers who want to orchestrate Datalore notebooks through AI assistants

Use cases

• Execute Jupyter notebooks on remote Datalore servers via AI agents
• Automate data analysis workflows by triggering notebook runs and collecting results
• Manage and retrieve files from Datalore project workspaces programmatically

Notes

This is a Model Context Protocol (MCP) server that wraps the Jetbrains Datalore API. It allows AI agents to run notebooks (including interactive runs), fetch run data, and retrieve files from cloud-based Datalore instances. The server acts as a bridge between MCP-compatible clients and the Datalore platform.

Use cases

• Execute Jupyter notebooks on remote Datalore servers via AI agents
• Automate data analysis workflows by triggering notebook runs and collecting results
• Manage and retrieve files from Datalore project workspaces programmatically

Pros

• Leverages the MCP standard for easy integration with AI assistants
• Provides direct access to Datalore’s cloud execution and file management capabilities
• Open-source implementation with a clear API wrapper

Cons

• Requires a running Jetbrains Datalore cloud instance to function
• Limited to the operations exposed by the Datalore API (run, interact, fetch files)
• Dependency on Datalore’s API availability and version compatibility

Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.