A Model Context Protocol (MCP) server for Context Engineering - file system as external memory for AI agents
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# Context Engineering MCP Server 这是一个符合 **Model Context Protocol (MCP)** 标准的服务器,旨在为 Claude Desktop、Cursor 或其他 AI 助手提供"外部记忆"和"上下文管理"能力。 它实现了 [Context Engineering](./ai-programming-best-practices.md) 的核心理念,允许 AI 像操作系统一样管理自己的工作区状态。 ## ✨ 功能 这个插件为你的 AI 助手添加了以下能力(Tools): 1. **`context_init`**: 初始化 `.ai/skills` 和 `.agent_memory` 目录结构。 2. **`context_state`**: 获取当前工作区的"快照"(包含目录树、Git状态、当前目标)。 3. **`context_save_observation`**: 将长输出(如日志、API响应)保存到文件,只返回摘要。 4. **`context_read_observation`**: 按需读取之前保存的观察结果。 ## 📦 安装与配置 ### 1. 作为 Python 包安装 ```bash # 从 PyPI 安装 pip install ctx-engine-mcp ``` ### 2. 配置 Claude Desktop 编辑你的 Claude Desktop 配置文件(通常位于 `~/Library/Application Support/Claude/claude_desktop_config.json`): ```json { "mcpServers": { "context-engineering": { "command": "uv", "args": [ "tool", "run", "--from", "ctx-engine-mcp", "context-mcp" ] } } } ``` 或者使用系统 Python: ```json { "mcpServers": { "context-engineering": { "command": "python3", "args": ["-m", "context_mcp.server"] } } } ``` ### 3. 配置 Cursor (即将支持) Cursor 目前正在积极集成 MCP,配置方式与 Claude Desktop 类似。 ## 🛠️ 使用示例 一旦配置完成,你可以在对话中直接告诉 Claude: > "初始化一下上下文环境" -> Claude 会调用 `context_init` > "现在的项目状态是什么?" -> Claude 会调用 `context_state` > "运行 npm install 并帮我分析错误,输出可能很长,请注意使用外部记忆" -> Claude 会运行命令并使用 `context_save_observation` 保存结果。
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