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    Plan your projects with The High Council! Several AI models from different labs argue about your idea, then debate on Software Engineering choices. The goal is to get everyone to work together, in harmony and with manners. Effectiveness is unproven, but it is a fun way to spend your tokens!
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    469 npm
    MIT
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    Enables remote control of the Cursor AI agent via chat platforms like GitHub Issues or Telegram, allowing users to start sessions and receive summaries and prompts in a chat thread.
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    75 npm
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    MIT
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    Enables an orchestrator like Claude Code to hand coding work off to Cursor SDK agents, run as detached background jobs that survive the session and can be listed, inspected, steered, resumed, or stopped. Agents are asynchronous and reusable across follow-up turns, letting expensive frontier models delegate cheaply without blocking or paying to read the results.
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    MIT
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    Enables Cursor to reach any number of child MCP servers through just five host tools and a staged catalog, so tool schemas stay off the host until a specific tool is needed and token spend stays low. Searches tool names, pulls a single schema on demand, then invokes it, while disabled children consume zero processes and zero schemas.
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    MIT
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    Enables centralized proxy and orchestration of MCP servers, providing unified tool discovery, authentication, and secure request routing. It adds a human-in-the-loop approval gate for high-risk actions and audit logging.
    Apache 2.0
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    MCP server that routes natural language requests to structured tool calls using a LoRA-tuned small language model, with built-in validation, retry, and fallback recovery.
    MIT
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    Enables agents to send only the handful of tool definitions relevant to each question, ranking a large catalog by keywords and optional embeddings to cut context cost and wrong-tool picks. It can also run in front of any mcpServers config as a proxy that exposes just search_tools and call_tool instead of the whole catalog.
    MIT