jupyter-mcp-server and chartmogul-mcp-server
These are ecosystem siblings within the MCP framework—one provides a general-purpose Jupyter integration server for executing code and accessing notebook kernels, while the other is a domain-specific server that exposes ChartMogul's SaaS API, both designed to be used as interchangeable MCP server implementations depending on the user's needs.
About jupyter-mcp-server
datalayer/jupyter-mcp-server
🪐 🔧 Model Context Protocol (MCP) Server for Jupyter.
Exposes Jupyter notebooks to AI clients via the Model Context Protocol through a rich toolset covering kernel management, multi-notebook operations, and cell execution with multimodal output support. Implements real-time notebook state synchronization with automatic error recovery, allowing AI agents to understand full notebook context and adjust execution dynamically. Integrates seamlessly with JupyterLab, JupyterHub, and cloud deployments while supporting any MCP-compatible client like Claude Desktop and Cursor.
About chartmogul-mcp-server
chartmogul/chartmogul-mcp-server
The MCP server for ChartMogul
Exposes ChartMogul's full API surface—including customer management, subscription operations, sales opportunities, and financial metrics like MRR, ARR, and LTV—as callable MCP tools. Implements Claude Desktop integration via stdio transport with token-based authentication, enabling AI agents to query accounts, manage customer records, and retrieve SaaS analytics without direct API calls. Built in Python and deployed through the `uv` package manager with local development support via MCP inspector.
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