经 AI Skill Hub 精选评估,executor MCP工具 获评「强烈推荐」。已获得 1.8k 颗 GitHub Star,这款MCP工具在功能完整性、社区活跃度和易用性方面表现出色,AI 评分 8.2 分,适合有一定技术背景的用户使用。
AI代理的集成层工具,支持调用任意OpenAPI和MCP服务。让AI智能体无缝对接第三方接口,实现自动化工作流。适合开发者和AI应用构建者扩展代理能力。
executor MCP工具 是一款遵循 MCP(Model Context Protocol)标准协议的 AI 工具扩展。通过 MCP 协议,它可以让 Claude、Cursor 等主流 AI 客户端直接访问和操作外部工具、数据源和服务,实现 AI 能力的无缝扩展。无论是文件操作、数据库查询还是 API 调用,都可以通过自然语言在 AI 对话中直接触发,极大提升生产效率。
AI代理的集成层工具,支持调用任意OpenAPI和MCP服务。让AI智能体无缝对接第三方接口,实现自动化工作流。适合开发者和AI应用构建者扩展代理能力。
executor MCP工具 是一款遵循 MCP(Model Context Protocol)标准协议的 AI 工具扩展。通过 MCP 协议,它可以让 Claude、Cursor 等主流 AI 客户端直接访问和操作外部工具、数据源和服务,实现 AI 能力的无缝扩展。无论是文件操作、数据库查询还是 API 调用,都可以通过自然语言在 AI 对话中直接触发,极大提升生产效率。
# 方式一:通过 Claude Code CLI 一键安装
claude skill install https://github.com/RhysSullivan/executor
# 方式二:手动配置 claude_desktop_config.json
{
"mcpServers": {
"executor-mcp--": {
"command": "npx",
"args": ["-y", "executor"]
}
}
}
# 配置文件位置
# macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
# Windows: %APPDATA%/Claude/claude_desktop_config.json
# 安装后在 Claude 对话中直接使用 # 示例: 用户: 请帮我用 executor MCP工具 执行以下任务... Claude: [自动调用 executor MCP工具 MCP 工具处理请求] # 查看可用工具列表 # 在 Claude 中输入:"列出所有可用的 MCP 工具"
// claude_desktop_config.json 配置示例
{
"mcpServers": {
"executor_mcp__": {
"command": "npx",
"args": ["-y", "executor"],
"env": {
// "API_KEY": "your-api-key-here"
}
}
}
}
// 保存后重启 Claude Desktop 生效
Connect any agent to everything.
Executor is an open-source integration layer for AI agents. Configure every integration once (MCP servers, OpenAPI specs, GraphQL APIs) with authentication and per-tool policies, then use that one catalog from any MCP-compatible agent.
Website · Documentation · Discord
https://github.com/user-attachments/assets/11225f83-e848-42ba-99b2-a993bcc88dad
The fastest path is Executor Cloud: sign in, add an integration, and point your agents at the hosted MCP endpoint. Nothing to install.
To run it locally instead (Node.js 20+):
npm install -g executor # or: pnpm add -g / bun add -g / yarn global add
executor install # install the durable background service
executor web # open the web UI in your browser
executor install keeps the service running across restarts. For a throwaway foreground runtime, use executor web --foreground. From the web UI, add your first integration and connect an agent.
npx add-mcp http://127.0.0.1:4788/mcp --transport http --name executor
npx add-mcp "executor mcp" --name executor ```
The Connect card in the web UI shows the exact command (and port, if it differs) already filled in. Most MCP clients only load servers at startup, so you may need to restart the client or open a new chat before the Executor tools appear.
executor install # install/start the durable background service
executor web # open the running web UI
executor web --foreground # start a temporary foreground runtime + web UI
executor daemon run # start persistent local daemon in background
executor daemon status # show daemon status
executor daemon stop # stop daemon
executor daemon restart # restart daemon
executor mcp # start MCP endpoint (stdio)
executor call <path...> '{"k":"v"}' # invoke a tool by path segments
executor call <path...> --help # browse namespaces/resources/methods
executor call <path...> --help --match "<text>" --limit <n> # narrow huge namespaces
executor resume --execution-id <id> # resume paused execution
executor tools search "<query>" # search tools by intent
executor tools sources # list configured sources + tool counts
executor tools describe <path> # show tool TypeScript/JSON schema
As part of my coding process, I give my agent access to references to other codebases to understand patterns and how other people have implemented systems. A non-exhaustive list:
You are also encouraged to use this codebase as a reference to understand how it is implemented.
From the web UI, click Add Source, paste an OpenAPI, GraphQL, or MCP URL, and Executor detects the type, indexes the tools, and handles auth. Or add one from the CLI:
executor call executor openapi addSource '{
"spec": "https://petstore3.swagger.io/api/v3/openapi.json",
"namespace": "petstore",
"baseUrl": "https://petstore3.swagger.io/api/v3"
}'
Use baseUrl when the OpenAPI document has relative servers entries (for example "/api/v3"). Confirm it is live with executor tools sources.
executor填补AI代理与外部服务的关键空白。架构清晰,支持灵活集成,1.8k星证明其实用价值。适合复杂自动化场景。
AI Skill Hub 为第三方内容聚合平台,本页面信息基于公开数据整理,不对工具功能和质量作任何法律背书。
建议在沙箱或测试环境中充分验证后,再部署至生产环境,并做好必要的安全评估。
✅ MIT 协议 — 最宽松的开源协议之一,可自由商用、修改、分发,仅需保留版权声明。
AI Skill Hub 点评:executor MCP工具 的核心功能完整,质量优秀。对于Claude Desktop / Claude Code 用户来说,这是一个值得纳入个人工具库的选择。建议先在非生产环境试用,再逐步推广。
| 原始名称 | executor |
| 原始描述 | 开源MCP工具:The missing integration layer for AI agents. Let them call any OpenAPI / MCP / G。⭐1.8k · TypeScript |
| Topics | MCP集成层OpenAPIAI代理自动化 |
| GitHub | https://github.com/RhysSullivan/executor |
| License | MIT |
| 语言 | TypeScript |
收录时间:2026-05-18 · 更新时间:2026-05-19 · License:MIT · AI Skill Hub 不对第三方内容的准确性作法律背书。
选择 Agent 类型,复制安装指令后粘贴到对应客户端