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Wisdom Layer MCP

by PV-Bhat
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智慧层MCP

由 LearnLM 提供支持的 Claude 元认知顾问。

概述

智慧层 MCP 是一个专门的模型上下文协议服务器，旨在增强 Claude 的推理能力。它创建了一个“智慧层”，充当 Claude 的战略提问者、顾问和复杂性降低者，帮助 Claude 避免重复犯错并取得更好的结果。

特征

  • 战略元认知顾问：分析克劳德的思维过程并提供有针对性的建议
  • 计划提炼：强制进行极其简化的总结，以保证清晰度和重点
  • 错误追踪：从过去的错误中吸取教训，避免将来再次犯错
  • LearnLM 集成：由 Google 的 LearnLM/Gemini API 提供支持，用于元认知指导

工具

1. wisdom_advise

一位不受约束的战略顾问，就像一位富有挑战性的导师：

  • 采用原始、未经过滤的背景来避免克劳德的认知偏见
  • 提供用户对齐检查并降低复杂性
  • 提出突破模式的问题和观点
  • 建议使用合适的 MCP 工具
  • 从过去的错误模式中吸取教训
<use_mcp_tool> <server_name>wisdom</server_name> <tool_name>wisdom_advise</tool_name> <arguments> { "plan": "My current plan is...", "userRequest": "Original request from user", "thinkingLog": "Raw sequential thinking output", "availableTools": ["tool1", "tool2"] } </arguments> </use_mcp_tool>

2. wisdom_canvas

最终计划的提炼工具：

  • 强制超简化计划表述
  • 包括“为什么”部分来证明方法的合理性
  • 在实施之前创建检查点
  • 执行过程中作为参考
<use_mcp_tool> <server_name>wisdom</server_name> <tool_name>wisdom_canvas</tool_name> <arguments> { "plan": "Detailed plan to distill", "userRequest": "Original request from user" } </arguments> </use_mcp_tool>

3. 智慧日志

错误跟踪系统：

  • 一句话描述所犯的错误和纠正的错误
  • 对重复出现的错误进行分类和统计
  • 创建持续的学习反馈循环
  • 由 LearnLM 阅读，提供有针对性的指导
<use_mcp_tool> <server_name>wisdom</server_name> <tool_name>wisdom_log</tool_name> <arguments> { "mistake": "One-sentence description of the mistake", "category": "mistake-category", "solution": "How it was corrected" } </arguments> </use_mcp_tool>

安装

先决条件

  • Node.js（v18.0.0 或更高版本）
  • npm（v7.0.0 或更高版本）
  • 用于 LearnLM 功能的 Gemini API 密钥

安装步骤

# Install globally npm install -g wisdom-layer-mcp # Or run directly npx wisdom-layer-mcp

MCP 配置

将服务器添加到您的 MCP 设置文件中。对于 Claude/Cline，通常位于：

  • 对于 Claude Desktop： ~/Library/Application Support/Claude/claude_desktop_config.json (macOS)
  • 对于 VSCode Cline： ~/.config/Code/User/globalStorage/saoudrizwan.claude-dev/settings/cline_mcp_settings.json (Linux)

添加以下配置：

{ "mcpServers": { "wisdom": { "command": "wisdom-layer-mcp", "args": [], "env": { "GEMINI_API_KEY": "your-gemini-api-key" }, "disabled": false, "autoApprove": [] } } }

使用模式

Claude 的理想使用模式：

  1. 克劳德运用顺序思维制定初步计划
  2. Claude 使用原始上下文调用 wisdom_advise
  3. Claude 根据 LearnLM 的建议改进了其方法
  4. Claude 最终选择了 wisdom_canvas 来实现超清晰效果
  5. 克劳德实施解决方案
  6. 克劳德在 wisdom_log 中记录所有学到的经验教训

这就创建了一个元认知层，帮助克劳德更好地思考自己的思维。

发展

# Clone the repository git clone https://github.com/yourusername/wisdom-layer-mcp.git cd wisdom-layer-mcp # Install dependencies npm install # Build npm run build # Start development mode npm run dev

执照

麻省理工学院

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hybrid server

The server is able to function both locally and remotely, depending on the configuration or use case.

克劳德的元认知顾问，提供战略指导、计划提炼和错误追踪，以增强克劳德的推理能力。

  1. 概述
    1. 特征
      1. 工具
        1. 1. wisdom_advise
        2. 2. wisdom_canvas
        3. 3. 智慧日志
      2. 安装
        1. 先决条件
        2. 安装步骤
        3. MCP 配置
      3. 使用模式
        1. 发展
          1. 执照

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