jupyter-mcp-server and mcp-server-memos-py
These are ecosystem siblings—both are MCP servers that extend Claude/LLM capabilities to different backend systems (Jupyter notebooks and Memos respectively), following the same protocol standard but serving distinct use cases.
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 mcp-server-memos-py
RyoJerryYu/mcp-server-memos-py
A Python package enabling LLM models to interact with the Memos server via the MCP interface for searching, creating, retrieving, and managing memos.
Implements the MCP protocol as a stdio-based server that exposes Memos operations (search, create, retrieve, tag management) as discrete tools callable by LLM clients. Supports token-based authentication and configurable visibility levels (PUBLIC/PROTECTED/PRIVATE) for memos, integrating seamlessly with MCP-compatible clients like Claude Desktop via Smithery or direct configuration.
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