经 AI Skill Hub 精选评估,开源MCP工具 获评「强烈推荐」。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 8.0 分,适合有一定技术背景的用户使用。
开源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。
开源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。
# 方式一:通过 Claude Code CLI 一键安装
claude skill install https://github.com/hatch3r/hatch3r
# 方式二:手动配置 claude_desktop_config.json
{
"mcpServers": {
"--mcp--": {
"command": "npx",
"args": ["-y", "hatch3r"]
}
}
}
# 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 开源MCP工具 执行以下任务... Claude: [自动调用 开源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": {
"__mcp__": {
"command": "npx",
"args": ["-y", "hatch3r"],
"env": {
// "API_KEY": "your-api-key-here"
}
}
}
}
// 保存后重启 Claude Desktop 生效
Crack the egg. Hatch better agents.
hatch3r is an open-source CLI and Cursor plugin that installs a battle-tested, tool-agnostic agentic coding setup into any repository. Ship Ready as of Cycle 8 (audit score 83.74/100, 0 Critical findings, 3 platform adapters wired, 21-domain governance audit cycle operational). One command gives you the full set of agents, skills, rules, commands, hooks, and MCP integrations -- optimized for your coding tool of choice (live counts in governance/inventory.json ). Selective init installs only what you need based on your project type and team size.
v1.9.0 scope cut: As of 1.9.0 hatch3r supports only Claude Code, Cursor, and GitHub Copilot. Twelve adapters were removed in a hard cut; canonical content is now read from the bundled npm package (no.agents/materialization in user repos), and the manifest moved to.hatch3r/hatch.json. See CHANGELOG.md for the full breaking-change list and migration notes.
Requires Node.js 22+.
npx hatch3r init
That's it. hatch3r detects your repo, asks about your project context (greenfield/brownfield, solo/team), lets you choose a content profile (minimal/standard/full/custom), and generates everything. The platform (GitHub, Azure DevOps, or GitLab) is auto-detected from your git remote. Run into issues? See Troubleshooting.
Since 1.7.5, MCP is opt-in. npx hatch3r init gates MCP behind a Yes/No prompt (default No) after the features picker. Declining the gate skips MCP entirely — no .env.mcp, no mcp.json, no servers in the manifest. When you accept the gate, hatch3r init creates a .env.mcp file with required environment variables for your selected MCP servers (gitignored by default) and writes MCP config to the tool-appropriate location (.cursor/mcp.json, .mcp.json, .vscode/mcp.json, etc.).
env object in .vscode/mcp.json.set -a && source .env.mcp && set +a && cursor .Manage MCP at any time via npx hatch3r mcp setup | list | remove <id> | env-check. See MCP Setup for full setup, per-server details, and PAT scope guidance.
npx hatch3r init # Interactive setup
npx hatch3r config # Reconfigure tools, MCP servers, features, and platform
npx hatch3r sync # Re-generate from canonical state
npx hatch3r update # Pull latest templates (safe merge)
npx hatch3r status # Check sync status between canonical and generated files
npx hatch3r validate # Validate bundled canonical content + on-disk adapter outputs
npx hatch3r verify # Drift check on adapter outputs (non-zero exit on drift)
npx hatch3r clean # Remove generated files (optional --reinit)
npx hatch3r worktree-setup <path> # Set up gitignored files in a worktree
npx hatch3r worktree-cleanup <path> # Clean up worktree-specific files
npx hatch3r cli-tools # Manage CLI tools (picker / list / install / detect)
npx hatch3r mcp # Manage MCP servers (setup / list / remove / env-check)
npx hatch3r add <pack> # Install a community pack (coming soon)
hatch3r cli-tools and hatch3r mcp are side-door entry points for users who skipped a section during init or want to revisit later. Each accepts subcommands: cli-tools defaults to opening the picker (list, install, detect are the other subcommands); mcp requires a subcommand (setup, list, remove <id>, env-check).
Since 1.7.5, hatch3r ships a first-class CLI-tools surface area as the token-efficient alternative to MCP. The picker runs during init (3 tiers grouped, tier-1 default-on, tier-2 conditional on detected project signals, tier-3 opt-in advanced). Detection probes each tool via command -v / where with a 2s timeout; the installer prints copy-paste commands grouped by package manager and never executes on your behalf. 5 essentials (ripgrep, jq, gh, fd, fzf) ship as standalone skills (skills/hatch3r-cli-{id}/SKILL.md); the remaining 24 tools live in a single category-indexed hatch3r-cli-toolbox skill, emitted to all 3 supported adapters.
Manage CLI tools at any time:
npx hatch3r cli-tools # open picker
npx hatch3r cli-tools list # selection + install status
npx hatch3r cli-tools install # print install commands for missing tools
npx hatch3r cli-tools detect # read-only detection report
See CLI Tools for the full 29-tool table, decision tree, and trade-off discussion vs MCP.
hatch3r provides a full project lifecycle, from setup to release:
npx hatch3r init detects your repo and platform, asks about context and profile, generates agents/skills/rules/commands/MCP. For headless CI, pass --yes with optional flags. See agentic process diagrams.hatch3r-board-init creates or connects a Projects V2 board with status fields, label taxonomy, and config writeback.todo.md at the project root (one item per line).hatch3r-board-fill parses todo.md, classifies items, groups into epics, builds a dependency DAG, and marks issues status:ready.hatch3r-board-groom surfaces stale items, priority imbalances, and decomposition candidates for selective refinement.hatch3r-board-pickup auto-selects the next issue by dependency order and priority, creates a branch, delegates implementation, and opens a PR.hatch3r-release determines the semver bump, generates a changelog, tags, and publishes.After init: For greenfield, runhatch3r-project-specthenhatch3r-roadmap. For brownfield, runhatch3r-codebase-map. For a single feature, runhatch3r-feature-plan. For small changes, runhatch3r-quick-change.
hatch3r includes a complete board management system supporting GitHub, Azure DevOps, and GitLab. Configure in hatch.json:
{
"board": {
"owner": "my-org",
"repo": "my-repo",
"projectNumber": 1,
"areas": ["area:frontend", "area:backend", "area:infra"]
},
"models": {
"default": "opus",
"agents": { "hatch3r-lint-fixer": "sonnet" }
}
}
hatch3r is also available as a Cursor plugin. Enable it for instant access to all rules, skills, agents, and commands without running init.
高质量的AI编码代理开发环境
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:开源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 | hatch3r |
| 原始描述 | 开源MCP工具:Production-ready spec driven development setup for AI coding agents in any repo 。⭐24 · TypeScript |
| Topics | AITypeScriptCLI |
| GitHub | https://github.com/hatch3r/hatch3r |
| License | MIT |
| 语言 | TypeScript |
收录时间:2026-05-26 · 更新时间:2026-05-26 · 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