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MCP工具
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MCP工具

MCP工具

基于 TypeScript · 让 AI 助手直接操作你的系统与工具
英文名:muggle-ai-works
⭐ 16 Stars 🍴 3 Forks 💻 TypeScript 📄 未公布协议 🏷 AI 8.0分
8.0AI 综合评分
ai-agentsai-powered-testingbrowser-automation
✦ AI Skill Hub 推荐

MCP工具 是 AI Skill Hub 本期精选MCP工具之一。综合评分 8.0 分,整体质量较高。我们强烈推荐将其纳入你的 AI 工具库,帮助提升工作效率。

📚 深度解析

MCP工具 是一款基于 MCP(Model Context Protocol)标准协议的 AI 工具扩展。MCP 协议由 Anthropic 开发并开源,旨在建立 AI 模型与外部工具之间的标准化通信接口,目前已被 Claude Desktop、Claude Code、Cursor 等主流 AI 工具采纳。

通过安装 MCP工具,你的 AI 助手将获得额外的工具调用能力,可以用自然语言直接操控该工具的功能,无需学习复杂的命令行语法。MCP 工具的核心价值在于"一次配置,永久增强"——配置完成后,每次与 AI 对话时都可以无缝调用这些工具。

在技术实现上,MCP 工具通过标准的 JSON-RPC 协议与 AI 客户端通信,工具的功能以"工具列表"的形式暴露给 AI 模型,AI 可以按需调用。MCP工具 提供了结构化的工具调用接口,使 AI 模型能够精确地理解和使用每个功能点,显著降低 AI 在工具使用上的错误率。

与传统的 API 集成相比,MCP 工具的优势在于无需编写代码——用户只需在配置文件中添加几行 JSON,即可让 AI 获得全新能力。AI Skill Hub 将 MCP工具 评为 AI 评分 8.0 分,属于同类工具中的优质选择。

📋 工具概览

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。

GitHub Stars
⭐ 16
开发语言
TypeScript
支持平台
Windows / macOS / Linux
维护状态
轻量级项目,按需更新
开源协议
未公布
AI 综合评分
8.0 分
工具类型
MCP工具
Forks
3

📖 中文文档

以下内容由 AI Skill Hub 根据项目信息自动整理,如需查看完整原始文档请访问底部「原始来源」。

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。

📌 核心特色
  • 通过标准 MCP 协议与 Claude、Cursor 等主流 AI 客户端深度集成
  • 提供结构化工具调用接口,显著降低 AI 集成复杂度
  • 支持 Claude Desktop 和 Claude Code 无缝接入,开箱即用
  • 可与其他 MCP 工具组合叠加,构建完整 AI 工作站
  • 轻量无侵入设计,不影响现有系统架构
🎯 主要使用场景
  • 在 Claude Desktop 对话中直接调用本地工具,实现 AI 与系统的深度联动
  • 通过自然语言驱动复杂的多步骤自动化任务,代替繁琐手动操作
  • 将多个 MCP 工具组合使用,构建个人专属 AI 工作站
以下安装命令基于项目开发语言和类型自动生成,实际以官方 README 为准。
安装命令
# 方式一:通过 Claude Code CLI 一键安装
claude skill install https://github.com/multiplex-ai/muggle-ai-works

# 方式二:手动配置 claude_desktop_config.json
{
  "mcpServers": {
    "mcp--": {
      "command": "npx",
      "args": ["-y", "muggle-ai-works"]
    }
  }
}

# 配置文件位置
# macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
# Windows: %APPDATA%/Claude/claude_desktop_config.json
📋 安装步骤说明
  1. 确认已安装 Node.js(v18 或以上版本)
  2. 打开 Claude Desktop 或 Claude Code 的 MCP 配置文件
  3. 按「交给 Agent 安装 → Claude Desktop」标签中的 JSON 配置填入 mcpServers 字段
  4. 保存配置文件并重启 Claude 客户端
  5. 重启后,在对话中即可使用本工具
以下用法示例由 AI Skill Hub 整理,涵盖最常见的使用场景。
常用命令 / 代码示例
# 安装后在 Claude 对话中直接使用
# 示例:
用户: 请帮我用 MCP工具 执行以下任务...
Claude: [自动调用 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"
以下配置示例基于典型使用场景生成,具体参数请参照官方文档调整。
配置示例
// claude_desktop_config.json 配置示例
{
  "mcpServers": {
    "mcp__": {
      "command": "npx",
      "args": ["-y", "muggle-ai-works"],
      "env": {
        // "API_KEY": "your-api-key-here"
      }
    }
  }
}

// 保存后重启 Claude Desktop 生效
📑 README 深度解析 真实文档 完整度 70/100 查看 GitHub 原文 →
以下内容由系统直接从 GitHub README 解析整理,保留代码块、表格与列表结构。

*muggle-ai-works*

Run real-browser E2E acceptance tests on your web app from any AI coding agent. Generate test scripts from plain English, replay them on localhost, capture screenshots, and validate user flows like signup, checkout, and dashboards. Works across Claude Code, Cursor, Codex, and Windsurf.

One install gives your AI coding assistant the power to exercise your app like a real user would: clicking through flows, catching broken experiences, and reporting results with screenshots and evidence.

License: MIT [npm]() [MCP Tools]() [Node]()

Powered by MuggleTest — the AI-powered E2E acceptance testing platform.

---

About

Built by the team behind MuggleTestAI-powered E2E acceptance testing for teams who ship fast.

Repository structure

muggle-ai-works/
├── plugin/                  # Claude Code plugin (source of truth)
│   ├── .claude-plugin/      #   Plugin manifest (plugin.json)
│   ├── skills/              #   Skill definitions
│   │   ├── muggle/                        # /muggle:muggle — command router and menu
│   │   ├── muggle-do/                     # /muggle:muggle-do — autonomous dev pipeline
│   │   ├── muggle-test-feature-local/     # /muggle:muggle-test-feature-local
│   │   ├── muggle-test-regenerate-missing/# /muggle:muggle-test-regenerate-missing
│   │   ├── muggle-status/                 # /muggle:muggle-status
│   │   ├── muggle-repair/                 # /muggle:muggle-repair
│   │   └── muggle-upgrade/                # /muggle:muggle-upgrade
│   ├── hooks/               #   Session hooks (hooks.json)
│   ├── scripts/             #   Hook scripts (ensure-electron-app.sh)
│   ├── .mcp.json            #   MCP server config
│   └── README.md            #   Plugin install and usage docs
│
├── src/                     # Application source
│   ├── cli/                 #   CLI commands (serve, setup, doctor, login, etc.)
│   └── server/              #   MCP server (tool registration, stdio transport)
│
├── packages/                # Workspace packages
│   ├── mcps/                #   Core MCP runtime — tool registries, schemas, services
│   ├── commands/            #   CLI command contracts and registration
│   └── workflows/           #   Workflow contracts and tests
│
├── scripts/                 # Build and release
│   ├── build-plugin.mjs     #   Assembles dist/plugin/ from plugin/ source
│   ├── verify-plugin-marketplace.mjs  # Validates plugin/marketplace consistency
│   ├── verify-compatibility-contracts.mjs # Validates long-term surface contracts
│   ├── verify-upgrade-experience.mjs  # Validates in-place upgrade behavior
│   └── postinstall.mjs      #   npm postinstall (Electron app download, Cursor MCP config, skills sync)
│
├── config/compatibility/     # Contract baselines (CLI/MCP/plugin/skills)
├── bin/                     # CLI entrypoint (muggle.js → dist/cli.js)
├── dist/                    # Build output (gitignored)
├── .claude-plugin/          # Marketplace catalog (marketplace.json)
└── docs/                    # Internal design docs and plans

Development commands

pnpm install              # Install dependencies
pnpm run build            # Build (tsup + plugin artifact)
pnpm run build:plugin     # Rebuild plugin artifact only
pnpm run verify:plugin    # Validate plugin/marketplace metadata consistency
pnpm run verify:contracts # Validate compatibility contracts (CLI/MCP/plugin/skills)
pnpm run verify:electron-release-checksums # Ensure checksums.txt exists for bundled electron release
pnpm run verify:upgrade-experience # Validate existing-user cleanup + re-download flow
pnpm run dev              # Dev mode (watch)
pnpm test                 # Run tests
pnpm run lint             # Lint (auto-fix)
pnpm run lint:check       # Lint (check only)
pnpm run typecheck        # TypeScript type check

CI/CD and publishing

WorkflowTriggerDescription
ci.ymlPush/PR to masterLint, test, build, plugin + compatibility contract verification on multiple platforms
verify-end-user-upgrade.ymlWeekly + manualExisting-user upgrade validation (cleanup + re-download + health checks)
publish-works-to-npm.ymlTag v* or manualVerify (including release checksums), audit, smoke-install, publish to npm

Publishing @muggleai/works: use the maintainer-only skill .claude/skills/muggle-works-npm-release/SKILL.md — a repo-local project skill (invoke /muggle-works-npm-release in Claude Code, or /mrelease, while working in this repo; mirrored to .cursor/skills/ for Cursor). It is intentionally not in the published plugin (plugin/skills/) since it is maintainer-only. It does the bump + pnpm run sync:versions, local verify, chore(release) PR, merge, then workflow_dispatch with an explicit version. Do not rely on tagging alone while package.json / marketplace manifests on master are still old — CI can publish a version that does not match the checked-in manifests. Tag v* push remains a valid workflow trigger when it matches the merged release commit.

Release tag strategy

  • electron-app-vX.Y.Z tags in muggle-ai-works are for public Electron app binary releases (consumed by muggle setup, muggle upgrade, and npm postinstall).
  • vX.Y.Z tags in muggle-ai-works are for npm publishing of @muggleai/works (publish-works-to-npm.yml).
  • muggle-ai-teaching-service builds Electron artifacts and publishes them into this public repo using electron-app-vX.Y.Z, so binaries are publicly downloadable.
  • The two version tracks are intentionally separate: runtime Electron artifact versions and npm package versions can move independently.

Optimizing agent-facing descriptions

AI agents decide which tools to use based on text in MCP server instructions, hook context injection, skill descriptions, tool descriptions, and plugin metadata. If these don't match what users actually say, agents won't reach for muggle tools.

The optimize-descriptions skill documents the full optimization process. It lives at internal/skills/optimize-descriptions/SKILL.md — an internal-only skill that does not ship via npm or the plugin marketplace. To use it as a slash command on a dev machine, symlink or copy the folder into ~/.claude/skills/. It covers:

  • The five layers of agent-facing text and where each lives in the codebase
  • How to write descriptions that match real user intent ("test my signup flow" not "execute test generation")
  • How to create trigger eval sets and run them with run_eval.py
  • Limitations of the eval tool (can't measure MCP instructions or hook injection)
  • A checklist for the full optimization workflow

Key files touched during optimization:

WhatFile
MCP server instructionssrc/server/mcp-server.ts
SessionStart hook injectionplugin/scripts/ensure-electron-app.sh
Hook configplugin/hooks/hooks.json
Skill descriptionsplugin/skills/*/SKILL.md
Tool descriptions (local)packages/mcps/src/mcp/tools/local/tool-registry.ts
Tool descriptions (cloud)packages/mcps/src/mcp/tools/e2e/tool-registry.ts
Plugin metadataplugin/.claude-plugin/plugin.json

Quick eval run:

```bash

4. Test a feature locally

Claude Code

Already have code running on localhost? Test it directly:

/muggle:muggle-test-feature-local

Describe what to test in plain English. The AI finds or creates test cases, launches a real browser, and reports results with screenshots.

Cursor/Codex/Windsurf/other MCP clients

Call local execution MCP tools directly (for example muggle-local-execute-test-script-replay or related muggle-local-* commands exposed by your client).

---

1. `/muggle:muggle-test-feature-local` — Test a feature on localhost

Describe what to test in English. The AI finds the right project and test cases, launches a real browser, and reports results with screenshots.

> /muggle:muggle-test-feature-local

"Test my login changes on localhost:3999"

1. Auth check ✓
2. Found project: "My App"
3. Found use case: "User Login"
4. Found 2 test cases — recommend replay (minor changes detected)
5. Launching browser test runner... (approve? y)
6. Results: 2/2 PASS
   Screenshots: ~/.muggle-ai/sessions/abc123/screenshots/
7. Publish to cloud? (y)

Requires Python 3.10+ and skill-creator plugin

cd ~/.claude/plugins/cache/claude-plugins-official/skill-creator/unknown/skills/skill-creator

python3 -m scripts.run_eval \ --eval-set /path/to/eval_set.json \ --skill-path /path/to/plugin/skills/test-feature-local \ --model claude-opus-4-6 \ --runs-per-query 3 \ --verbose ```

See internal/skills/optimize-descriptions/SKILL.md for the full guide.

---

1. Install skills and mcps (choose your client)

Claude Code (full plugin experience)

/plugin marketplace add https://github.com/multiplex-ai/muggle-ai-works
/plugin install muggleai@muggle-works

This installs:

  • /muggle:muggle — command router and menu
  • /muggle:muggle-do — autonomous dev pipeline (requirements to PR)
  • /muggle:muggle-test — change-driven E2E acceptance testing (local or remote, with PR posting)
  • /muggle:muggle-test-feature-local — local quick E2E acceptance testing
  • /muggle:muggle-test-regenerate-missing — bulk-regenerate test scripts for every test case that has no active script
  • /muggle:muggle-status — health check for muggle-works plugins (Electron app, MCP server, and auth)
  • /muggle:muggle-repair — diagnose and fix broken installation
  • /muggle:muggle-upgrade — update to the latest version
  • MCP server with 70+ tools (auto-started)
  • Electron browser test runner provisioning (via session hook)

Cursor, Codex, Windsurf, and other MCP clients (MCP tools only)

npm install -g @muggleai/works

For Cursor, that's it — the install automatically configures ~/.cursor/mcp.json and syncs muggle-* skills to ~/.cursor/skills/. Just restart Cursor.

For other MCP clients, add this to your client's config:

{
  "mcpServers": {
    "muggle": {
      "command": "muggle",
      "args": ["serve"],
      "env": {
        "MUGGLE_MCP_PROMPT_SERVICE_TARGET": "production"
      }
    }
  }
}

Claude slash commands are plugin-managed, so update those with /plugin update muggleai@muggle-works.

3. Start building features

Claude Code

Describe what you want to build:

/muggle:muggle-do "Add a logout button to the header"

The AI handles the full cycle: code the feature, run unit tests, run E2E acceptance tests against the app in a real browser, and open a PR with results.

Cursor/Codex/Windsurf/other MCP clients

Use the direct MCP workflow section below to call muggle-* tools from your client.

3. Direct MCP tool calls — Build your own E2E acceptance workflow

Use any of the 70+ MCP tools directly from your AI assistant. This is the lowest-level option and the most flexible for building custom E2E acceptance workflows.

"Create a project called My App with URL https://myapp.com"
"Generate test cases for the checkout flow"
"Replay all test scripts against localhost:3000"
"Show me the latest E2E acceptance results"

---

Setup and Diagnostics

muggle setup # Download/update browser test runner muggle setup --force # Force re-download muggle doctor # Diagnose installation issues

Setup and Configuration

Authentication happens automatically when you first use a tool that requires it: a browser window opens with a verification code, you log in with your Muggle AI account, and the tool call continues. Credentials persist across sessions in ~/.muggle-ai/.

MCP client configuration examples

When installed as a plugin, MCP server configuration is shipped by the plugin (plugin/.mcp.json) and does not require manual user-level file copy.

Environment targeting — set MUGGLE_MCP_PROMPT_SERVICE_TARGET to switch between production and dev:

{
  "mcpServers": {
    "muggle": {
      "command": "muggle",
      "args": ["serve"],
      "env": {
        "MUGGLE_MCP_PROMPT_SERVICE_TARGET": "production"
      }
    }
  }
}

Multi-repo config for /muggle:muggle-do — create muggle-repos.json in your working directory:

[
  { "name": "frontend", "path": "/absolute/path/to/frontend", "testCommand": "pnpm test" },
  { "name": "backend", "path": "/absolute/path/to/backend", "testCommand": "pnpm test" }
]

Data directory structure (~/.muggle-ai/)

~/.muggle-ai/
├── oauth-session.json    # OAuth tokens (short-lived, auto-refresh)
├── api-key.json          # Long-lived API key for service calls
├── projects/             # Local project cache
├── sessions/             # E2E test sessions
│   └── {runId}/
│       ├── action-script.json    # Recorded browser steps
│       ├── results.md            # Step-by-step report
│       └── screenshots/          # Per-step images
└── electron-app/         # Downloaded browser test runner
    └── {version}/

---

Quick Start

CLI Reference

```bash

2. `/muggle:muggle-do` — Autonomous dev pipeline

Full development cycle: requirements to PR in one command. The AI codes the feature, writes unit tests, runs E2E acceptance tests against your running app, and opens a PR.

> /muggle:muggle-do "Add a logout button to the header"

REQUIREMENTS  → Goal: Add logout button. Criteria: visible, functional, redirects.
IMPACT        → frontend repo, src/components/Header.tsx
VALIDATE      → Branch: feat/add-logout, 1 commit
CODING        → (writes/fixes code)
UNIT_TESTS    → 12/12 pass
E2E acceptance → 3/3 test cases pass
OPEN_PRS      → PR #42 opened
DONE          → 1 iteration, all green
  • Session-based with crash recovery (~/.muggle-ai/muggle-do/sessions/)
  • Auto-triage: analyzes failures and loops back to fix (max 3 iterations)
  • Multi-repo support via muggle-repos.json
  • PRs include E2E acceptance results and screenshots in the description
🎯 aiskill88 AI 点评 A 级 2026-06-24

高质量的AI驱动的Web测试工具

📚 实用指南(长尾问题)
适合谁
  • 构建多智能体协作系统的 Agent 开发者
最佳实践
  • Agent 任务先做 dry-run 验证工具调用链,再开启自主执行
常见错误
  • API key 直接提交到 git 仓库(请用 .env 并加入 .gitignore)
部署方案
  • 云端托管:可放在 Vercel / Railway / Fly.io 等 PaaS 平台
相关搜索
muggle-ai-works 中文教程muggle-ai-works 安装报错怎么办muggle-ai-works Agent 工作流muggle-ai-works 与同类工具对比muggle-ai-works 最佳实践muggle-ai-works 适合谁用

⚡ 核心功能

👥 适合谁
  • 构建多智能体协作系统的 Agent 开发者
⭐ 最佳实践
  • Agent 任务先做 dry-run 验证工具调用链,再开启自主执行
⚠️ 常见错误
  • API key 直接提交到 git 仓库(请用 .env 并加入 .gitignore)

👥 适合人群

Claude Desktop / Claude Code 用户AI 工具开发者需要扩展 AI 能力的专业人士自动化工程师

🎯 使用场景

  • 在 Claude Desktop 对话中直接调用本地工具,实现 AI 与系统的深度联动
  • 通过自然语言驱动复杂的多步骤自动化任务,代替繁琐手动操作
  • 将多个 MCP 工具组合使用,构建个人专属 AI 工作站

⚖️ 优点与不足

✅ 优点
  • +标准化 MCP 协议,生态互联性强
  • +与 Claude 官方生态无缝对接
  • +即插即用,配置简单快捷
⚠️ 不足
  • 未明确开源协议,商用场景需谨慎评估
  • 依赖 Claude 客户端,非 Claude 用户无法使用
  • MCP 协议仍在持续演进,接口可能变更
  • 需要一定的配置步骤
⚠️ 使用须知

该工具未明确声明开源协议,商业使用前请联系原作者确认授权范围,避免侵权风险。

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。

🔗 相关工具推荐

🧩 你可能还需要
基于当前 Skill 的能力图谱,自动补全的工具组合

❓ 常见问题 FAQ

MCP工具是一种开源的AI驱动的Web产品测试工具
💡 AI Skill Hub 点评

经综合评估,MCP工具 在MCP工具赛道中表现稳健,质量优秀。如果你已有明确的使用需求,可以直接上手体验;如果还在评估阶段,建议对比同类工具后再做决策。

⬇️ 获取与下载
⚠️ 该工具未声明开源协议,不提供直接下载。请访问原项目了解使用条款。
📚 深入学习 MCP工具
查看分步骤安装教程和完整使用指南,快速上手这款工具
🌐 原始信息
原始名称 muggle-ai-works
原始描述 开源MCP工具:Your AI coding agent writes code fast — we make sure the web product actually wo。⭐16 · TypeScript
Topics ai-agentsai-powered-testingbrowser-automation
GitHub https://github.com/multiplex-ai/muggle-ai-works
语言 TypeScript
🔗 原始来源
🐙 GitHub 仓库  https://github.com/multiplex-ai/muggle-ai-works 🌐 官方网站  https://www.muggletest.com/

收录时间:2026-06-24 · 更新时间:2026-06-24 · License:未公布 · AI Skill Hub 不对第三方内容的准确性作法律背书。

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