Hey! I just launched YAMCP (pronounced “YAM-C-P”), an open-source CLI that bundles any number of Model Context Protocol (MCP) servers, local or remote, into unified local workspaces for your AI apps.<p>The problem yamcp intends to solve: Juggling multiple MCP servers across different AI tools means editing different config files and digging through separate log files whenever something breaks.<p>What it offers: YAMCP lets you create dedicated “YAM” workspaces organized however works best for your work styles, by function (e.g. coding, design, research), by app (Cursor, Claude, GitHub-Copilot), or any custom combination in between and expose them as Yet-Another-MCP. Scan an entire YAM workspace for issues, connect your AI apps to a single gateway, and manage everything from one simple gateway.<p>Why YAMCP?
* Organize your servers locally: Group MCP server by AI application or workflow purpose.<p>* Scan and Catch errors early: Scan workspaces for misconfigurations before they disrupt your work.<p>* Single gateway per each workspace: Point all your AI tools at one MCP instead of constantly swapping servers and manage your servers through a single cli environment locally.<p>* Unified management Add, remove, and update servers with a cli command.<p>* Centralized logging to debug all servers from one place. Track every request and response across all your MCP connections in one place.<p>Check out the repo for install steps and examples: <a href="https://github.com/hamidra/yamcp">https://github.com/hamidra/yamcp</a><p>Planning to add server evaluations and an initial security scan to score MCP servers’ reliability and performance.<p>Would love for you to try it and share what features you’d like to see next!