Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
作者提供的说明(英文原文)
Wrap any CLI as a Model Context Protocol server - schema auto-inferred from --help.
这三项永远不会合并成一个分数:意见、测量和人气是不同的东西。
我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。
选择你使用的 AI 应用,然后复制设置。
你需要
你用的是哪个应用?
在上方选择你的应用。我们会记住它,下次按钮会显示“安装到 …”。
打开 Claude Desktop → Settings → Developer → Edit Config,把下面的内容粘贴到 claude_desktop_config.json
{
"mcpServers": {
"cli2mcp": {
"command": "npx",
"args": [
"-y",
"cli2mcp"
]
}
}
}在终端中运行这条命令
claude mcp add cli2mcp -- npx -y cli2mcp这个服务器需要在启动命令中填入值,请复制设置后自行填写。
粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json
{
"mcpServers": {
"cli2mcp": {
"command": "npx",
"args": [
"-y",
"cli2mcp"
]
}
}
}浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。
这个服务器需要在启动命令中填入值,请复制设置后自行填写。
粘贴到项目中的 .vscode/mcp.json
{
"servers": {
"cli2mcp": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"cli2mcp"
]
}
}
}浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。
这个服务器在你的电脑上运行,而 ChatGPT 只能连接互联网上的服务器。请选择其他应用。
你的选择通过 Cookie 保存在这台设备上,无需账户。
这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同,请以 README 为准。
它在你的电脑上运行;安装后,工具列表会显示在你的 AI 应用中。
我们检查的是任何人都能看到的信息;我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月6日
注册名称已通过 GitHub 账户 RonieNeubauer 验证,该账户拥有此仓库
我们还没有从 GitHub 读取这个仓库
我们还没有从 GitHub 读取这个仓库
它在你的电脑上运行,没有互联网端点
在你的电脑上运行,改用本地设置
它在你的电脑上运行;我们只能读取互联网端点的工具列表
与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时,星标数才计入。
它在 1 项适用的基础检查中通过了 1 项。我们没有阅读代码。在添加密钥或令牌之前,请先看看这个服务器要求哪些权限,并使用只具备所需权限的密钥。
注册中心没有列出必需的密钥,不过有些服务器会在首次使用时要求你登录。
它在你的电脑上运行。你的 AI 应用会在需要时启动它,数据不会经过作者的服务器(除非它自己调用在线服务)。
GitHub 仓库最后更新于–,最新版本(0.1.4)于7个月前进入注册中心。
支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。你的电脑上还需要有 Node.js。
同一分类中有:Spec Driven Development, Remote Desktop Commander, Safe Fetch
同一分类中其他作者的服务器,按星标数排序。
如何看卡片:★ GitHub 星标i三大支柱:评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.
MCP server for fetching URLs, safe against SSRF, DNS rebinding, and redirect-to-internal attacks.
按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。
Status: v0.1 — early release. Stdio transport only. APIs may change before 1.0.
Expose any command-line binary as a Model Context Protocol tool by parsing its --help output and synthesizing a JSON Schema at startup. One command, no boilerplate.
Works with any MCP-compatible client — Claude Desktop, ChatGPT (via OpenAI Agents SDK), Cursor, Gemini CLI, Cline, Windsurf, Continue, Zed, and anything else that speaks the MCP stdio transport.
npx cli2mcp <command>
Writing an MCP server for a CLI you already have is mechanical work: instantiate the SDK, register a tool, hand-write the input schema, marshal arguments, spawn the subprocess, format the output. Roughly 80–150 lines of TypeScript per binary, repeated forever as new tools come out.
cli2mcp does it in one command. The CLI's own --help is the source of truth for the schema — if rg adds a flag tomorrow, the AI sees it tomorrow without code changes.
npm install -g cli2mcp
npx cli2mcp
Requires Node.js 22+.
cli2mcp is launched by your client as a stdio subprocess. Add an entry per CLI you want to expose.
Config file location:
| OS | Path |
|---|---|
| macOS | ~/Library/Application Support/Claude/claude_desktop_config.json |
| Windows | %APPDATA%\Claude\claude_desktop_config.json |
| Linux | ~/.config/Claude/claude_desktop_config.json |
{
"mcpServers": { "ripgrep": { "command": "npx", "args": ["-y", "cli2mcp", "rg", "--name", "ripgrep"] }, "jq": { "command": "npx", "args": ["-y", "cli2mcp", "jq"] } } }
Restart Claude Desktop after editing.
| Client | Config file | Format |
|---|---|---|
| ChatGPT (OpenAI Agents SDK) | MCPServerStdio parameter — see OpenAI Agents docs | command: "npx", args: ["-y", "cli2mcp", " "] |
| Cursor | .cursor/mcp.json (project) or ~/.cursor/mcp.json (global) | Same mcpServers block as above |
| Cline | VS Code → Cline → MCP Settings → cline_mcp_settings.json | Same mcpServers block |
| Windsurf | ~/.codeium/windsurf/mcp_config.json | Same mcpServers block |
| Gemini CLI | ~/.gemini/settings.json | Same mcpServers block |
| Continue | ~/.continue/config.json → experimental.modelContextProtocolServers | Same launcher |
| Zed | ~/.config/zed/settings.json → context_servers | Same launcher |
| Any stdio-capable MCP client | per the client's docs | Same launcher: npx -y cli2mcp |
Refer to each client's documentation for the exact config path on your platform — they evolve and are not guaranteed to match the table above.
Drop any of these into your client's mcpServers block (paths shown above per client). Each one wraps a popular CLI as an MCP tool an AI can call directly.
{
"mcpServers": { "ripgrep": { "command": "npx", "args": ["-y", "cli2mcp", "rg", "--name", "ripgrep", "--description", "Recursively search files with regex"] }, "jq": { "command": "npx", "args": ["-y", "cli2mcp", "jq", "--description", "Query and transform JSON via stdin"] }, "pandoc": { "command": "npx", "args": ["-y", "cli2mcp", "pandoc", "--description", "Convert documents between markup formats"] }, "sqlite3": { "command": "npx", "args": ["-y", "cli2mcp", "sqlite3", "--description", "Run SQL against a SQLite database file", "--cwd", "/path/to/safe/dir"] }, "yt-dlp": { "command": "npx", "args": ["-y", "cli2mcp", "yt-dlp", "--description", "Download media from URLs", "--cwd", "/path/to/downloads", "--timeout", "300000"] } } }
Each CLI must already be installed and on
PATH.cli2mcpdoes not install them for you.
| Approach | LOC per CLI | New flag handling | Maintenance |
|---|---|---|---|
| Hand-written MCP server (TypeScript SDK) | ~80–150 | manual schema edit | per-CLI release cycle |
| OpenAPI → MCP generators | n/a | requires an OpenAPI spec | does not cover arbitrary CLIs |
Wrapping bash / sh as a tool | ~10 | n/a — gives the AI a shell | unsafe, no schema, no sandbox |
| `cli2mcp ` | 0 | automatic at next start | none — re-reads `--help` |
The closest neighbor is FastMCP's from_openapi — it does not cover arbitrary CLI binaries. As of April 2026 there is no other published tool that turns an arbitrary --help output into a typed MCP tool in one command.
These CLIs are covered by the test suite or have been manually exercised end-to-end:
| CLI | Status | Notes |
|---|---|---|
jq | ✅ tested | help-on-stderr correctly captured; stdin piping works |
ripgrep (rg) | ✅ tested | 90+ flags inferred; args positional handled |
curl | ✅ fixture | shape extraction validated against bundled fixture |
node | ✅ integration test | end-to-end MCP handshake + tools/call |
Other POSIX-style CLIs (e.g. ffmpeg, yt-dlp, pandoc, sqlite3, imagemagick) are *expected* to work but are not yet covered by tests. Report bugs in issues.
| Help fragment | MCP property |
|---|---|
--flag | boolean |
--flag / / | string |
--flag / / | number |
--flag | string enum with choices |
| Repeatable flag | array |
| Positional args | args: array |
Reserved input stdin | string piped to subprocess stdin |
When parsing fails on an unconventional --help, cli2mcp falls back to a single variadic args positional so the tool is still usable — the model just gets a free-form argument list instead of typed flags.
cli2mcp <command> [options]
--name Tool name shown to the AI (default: ) --description Tool description shown to the AI (default: first --help line) --timeout Subprocess timeout per call (default: 60000) --cwd Working directory for subprocess (default: process.cwd()) --env Extra environment variables (repeatable) --stderr stderr handling: include → appended to tool output (default) drop → discarded error → any stderr → isError: true -h, --help Show help
Reserved input property stdin is piped to the subprocess:
{ "args": [".name"], "stdin": "{\"name\": \"cli2mcp\"}" }
cli2mcp rg
│ ├─ 1. spawn: rg --help → capture stdout + stderr ├─ 2. parse help text → CliShape { flags, positionals, description } ├─ 3. synthesize JSON Schema → inputSchema ├─ 4. register one MCP tool → name: "rg", schema: └─ 5. start stdio MCP server → await client connection
On tools/call: { args, flags, stdin? } → argv builder → execa(rg, argv, { stdin }) │ stdout (+ stderr) → content[text]
Non-zero exit → { isError: true, content: [{ type: "text", text: }] } (unless --stderr drop).
cli2mcp lets an AI agent invoke the CLIs you expose, with the arguments the agent chooses. You are responsible for what those CLIs can do on your machine.
Practical guidance:
jq, rg, pandoc are mostly safe (read-only, deterministic). curl, ffmpeg --output, sqlite3, rm, kubectl, aws are not.curl to fetch evil.example.com, an exposed rm to delete files, etc.cli2mcp provides.The schema-from-help design *reduces* the risk of malformed argv but does not eliminate the risk of misuse. Treat each exposed CLI as a delegated capability, not a sandbox.
The CLI has no `--help` flag. cli2mcp will still start with a single args positional. The AI can pass arguments freely; you lose typed flag inference.
The schema came out empty / wrong. Run cli2mcp manually and inspect the tools/list response (use npx @modelcontextprotocol/inspector). The most common cause is non-standard help formatting (no --long-form flags, columns misaligned). Open an issue with the --help output attached.
The subprocess hangs. The default 60s timeout will kill it. Raise via --timeout. If your CLI is interactive (waits for a TTY), cli2mcp cannot help — pipe input via stdin instead.
Flag not being passed. Set --stderr include (the default) and inspect the content[].text. If the flag isn't appearing in argv, the help parser failed to extract it — file an issue.
Bug reports and patches welcome. Fixtures for new CLIs (test/fixtures/help/ .txt + a shape test) are the highest-leverage contributions.
pnpm install
pnpm test # vitest pnpm typecheck # tsc --noEmit pnpm lint # biome check
If cli2mcp saved you an afternoon of writing MCP boilerplate, a star helps other people find it.
Built by Ronie Neubauer — Principal Engineer, 22+ years shipping production systems.
MIT © 2026 Ronie Neubauer.