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impart-mcp

v1.0.7

Published

MCP server for AI agent orchestration - integrate Claude Code, Codex CLI, and Gemini CLI as expert agents

Readme

Impart MCP (Agent Orchestration Layer)

TypeScript Bun Node.js MCP npm

impart-mcp 是一个基于 Model Context Protocol (MCP) 的智能体编排服务器。它充当「Agent 编排层」,将具备高度工程化能力的专家智能体(如 Claude Code, Codex CLI 等)封装为标准 MCP 工具,使宿主环境(Claude Desktop, Cursor 等)能够通过统一接口调用这些具备复杂任务处理能力的「超级 Agent」。

🚀 核心特性

  • 多智能体编排:内置 5 种预设专家提示词和工具权限的专业 Agent。
  • 跨平台集成:完美适配 Claude Desktop, Cursor, Gemini CLI 等支持 MCP 的环境。
  • 异步任务处理:支持耗时任务的后台运行与结果轮询。
  • 混合模型供应商:集成 Vercel AI SDK,支持 Claude Code、Codex CLI 和 Gemini CLI 驱动的 Agent。
  • 灵活配置:通过 JSON 配置文件自定义每个 Agent 的模型、开关及参数。

🛠️ 专家智能体 (Agents)

| Agent 名称 | 核心定位 | 默认模型 | 权限 | |:---|:---|:---|:---| | Advisor | 架构与调试专家,处理高难度工程问题 | codex/gpt-5.2 | Read-only | | Researcher | 代码研究专家,擅长跨仓搜索与文档分析 | claude/sonnet | Read-only | | Explore | 代码定位专家,快速回答「某逻辑在哪里」 | gemini/gemini-3-flash-preview | Read-only | | Frontend Engineer | UI/UX 实现专家,独立完成高保真组件 | gemini/gemini-3-pro-preview | Read-write | | Document Writer | 技术文档专家,撰写清晰的规范文档 | gemini/gemini-3-flash-preview | Read-write |

📦 安装说明

方式一:npx 直接运行(推荐)

无需安装,直接在 MCP 配置中使用:

npx impart-mcp@latest

方式二:全局安装

npm install -g impart-mcp
# 或
bun add -g impart-mcp

方式三:从源码安装

前置要求:BunNode.js >= 18

git clone <repository-url>
cd impart-mcp
bun install  # 或 npm install
bun run build  # 构建产物

🔌 使用集成

配置到 Cursor

  1. 打开 Cursor 设置 -> Features -> MCP。
  2. 添加新的 MCP Server。
  3. Name: impart-mcp
  4. Type: command
  5. Command: npx impart-mcp@latest(或全局安装后直接使用 impart-mcp

配置到 Claude Code

使用 claude mcp add 命令一键添加:

claude mcp add impart-mcp -- npx impart-mcp@latest

或全局安装后:

claude mcp add impart-mcp -- impart-mcp

⚙️ 配置说明

默认情况下,所有 Agent 使用内置的默认配置即可运行,无需额外配置。

自定义配置(可选)

如需自定义 Agent 的模型或开关,可通过环境变量 AGENT_CONFIG_PATH 指定配置文件路径:

{
  "mcpServers": {
    "impart-mcp": {
      "command": "npx",
      "args": ["impart-mcp@latest"],
      "env": {
        "AGENT_CONFIG_PATH": "/path/to/your/agent-config.json"
      }
    }
  }
}

自动初始化:若指定的配置文件不存在,系统会在首次运行时自动生成包含所有默认值的配置模板,方便你按需修改。

配置文件示例 (agent-config.json):

{
  "advisor": {
    "model": "codex/gpt-5.2",
    "enabled": true
  },
  "researcher": {
    "model": "claude/sonnet",
    "enabled": true
  },
  "frontend-ui-ux-engineer": {
    "model": "gemini/gemini-3-pro-preview",
    "enabled": true
  }
}

📋 API 文档 (MCP Tools)

服务器提供了以下核心工具:

| 工具名称 | 类型 | 描述 | |:---|:---|:---| | call_agent | 同步 | 阻塞式调用,适用于需要立即验证结果的场景 | | call_agent_async | 异步 | 后台启动任务,返回 task_id,推荐用于耗时较长的搜索任务 | | get_agent_result | 查询 | 获取异步任务状态,支持 block 模式阻塞等待 | | call_agents_batch | 批量 | 并行调用多个 Agent,阻塞直到所有任务完成 |

参数说明

call_agent / call_agent_async

  • agent:Agent 名称枚举 (advisor | researcher | explore | frontend-ui-ux-engineer | document-writer)
  • prompt:任务描述
  • cwd:工作目录(必填)
  • context:可选上下文信息

👨‍💻 开发说明

| 命令 | 描述 | |:---|:---| | bun start | 启动服务(Bun 运行时)| | bun dev | 开发模式(支持热重载)| | bun run build | 构建产物到 dist/ | | node dist/server.js | 启动服务(Node.js 运行时)|

核心逻辑路径

| 文件 | 职责 | |:---|:---| | src/server.ts | MCP 协议处理与工具注册 | | src/agents/ | Agent 的 System Prompt 及行为定义 | | src/providers/ | 模型供应商适配逻辑 | | src/types.ts | 全局类型定义 |

📄 许可证

MIT License