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lingjing-classroom-mcp

v1.0.2

Published

LingJing Classroom — a deterministic (no-LLM) knowledge & blindspot MCP for AI agents: a teaching loop that returns 7-dimension blindspots and a summary. An independent gap-check layer, never hallucinates, never grades.

Readme

灵境 LingJing · 课室 MCP

一间课室:人当老师,AI 当学生。你把知识/经验/技能教给 AI,它从各角度追问,课后交回盲区、总结和可带走的卡。

灵境(LingJing)本身是一个网页课室产品(本地优先,不部署)。本仓库是它的 MCP 接口包装:让任意 AI Agent 通过 MCP stdio 直接开课室、授课、收反思。

快速开始

npx lingjing-classroom-mcp

然后在支持 MCP 的客户端里添加(stdio):

{
  "mcpServers": {
    "lingjing": {
      "command": "npx",
      "args": ["lingjing-classroom-mcp"]
    }
  }
}

工具

| 工具 | 作用 | |---|---| | lingjing_start_session | 开课室,返回 sessionId | | lingjing_teach | 老师授课:把内容发给 AI 学生,返回苏格拉底式追问 | | lingjing_reflect | 课后反思:返回盲区(未覆盖的认知维度)、总结、可带走的卡 | | lingjing_close_session | 下课:关闭课室并交回最终总结 |

设计说明

  • 确定性引擎:无需 LLM、无需联网、可离线复现(与灵境 server.js 的「确定性兜底」一致)。配置真实 LLM 学生属于灵境本体能力,本 MCP 包装提供的是可审计的确定性课室循环。
  • 盲区判定:基于 7 个认知维度(前提/假设、反例/边界、因果方向、不确定性/误差、适用范围/人群、长期演化、价值/责任)做覆盖度检查。
  • 诚实降级:维度未覆盖即如实列为盲区,不编造结论。

许可

UNLICENSED —— 非商业免费,商业须版权人书面授权。详见 LICENSE。