Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Descripción del creador (original en inglés)
Wrap any CLI as a Model Context Protocol server - schema auto-inferred from --help.
Estos tres nunca se combinan en una sola puntuación: las opiniones, las mediciones y la popularidad son cosas distintas.
Todavía no escribimos un resumen sencillo para este. Abajo están los datos que leímos del registro.
Elige la app de IA que usas y copia la configuración.
Necesitas
¿Qué app usas?
Elige tu app arriba. La recordamos, así que la próxima vez el botón dirá “Instalar en …”.
Abre Claude Desktop → Settings → Developer → Edit Config y pega esto en claude_desktop_config.json
{
"mcpServers": {
"cli2mcp": {
"command": "npx",
"args": [
"-y",
"cli2mcp"
]
}
}
}Ejecuta esto en tu terminal
claude mcp add cli2mcp -- npx -y cli2mcpEste necesita valores en su línea de comandos, así que copia la configuración y complétalos.
Pégalo en .cursor/mcp.json de tu proyecto, o en ~/.cursor/mcp.json
{
"mcpServers": {
"cli2mcp": {
"command": "npx",
"args": [
"-y",
"cli2mcp"
]
}
}
}Tu navegador te pide permiso para abrir la app; luego la app muestra la configuración y te pide confirmar. Los valores de las claves quedan vacíos para que los completes tú.
Este necesita valores en su línea de comandos, así que copia la configuración y complétalos.
Pégalo en .vscode/mcp.json de tu proyecto
{
"servers": {
"cli2mcp": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"cli2mcp"
]
}
}
}Tu navegador te pide permiso para abrir la app; luego la app muestra la configuración y te pide confirmar. Los valores de las claves quedan vacíos para que los completes tú.
Este se ejecuta en tu computadora, y ChatGPT solo puede conectarse a servidores en internet. Elige otra app.
Tu elección se guarda en una cookie en este dispositivo; no necesitas cuenta.
Esta configuración se genera a partir de la ficha del creador en el registro. Si el README dice otra cosa, sigue el README.
Se ejecuta en tu computadora; la lista de herramientas aparece en tu app de IA después de instalarlo.
Revisamos información que cualquiera puede ver; no hemos leído el código. Las revisiones que no aplican no se cuentan. · Revisado el 6 nov 2026
El nombre en el registro se verificó con la cuenta de GitHub RonieNeubauer, dueña del repo
Todavía no hemos leído este repo en GitHub
Todavía no hemos leído este repo en GitHub
Este se ejecuta en tu computadora; no hay endpoint en internet
Se ejecuta en tu computadora y usa ajustes locales en su lugar
Se ejecuta en tu computadora; solo podemos leer listas de herramientas de endpoints en internet
Comparado con todos los servidores activos de esta categoría en el registro. Las estrellas solo cuentan cuando quien lo publica es dueño del repo.
Superó 1 de 1 revisiones básicas aplicables. No hemos leído el código. Antes de agregar una clave o un token, revisa qué acceso pide el servidor y usa una clave que tenga solo los permisos que necesitas.
El registro no indica ninguna clave obligatoria, aunque algunos servidores te piden iniciar sesión la primera vez que los usas.
Se ejecuta en tu computadora. Tu app de IA lo inicia cuando hace falta, y los datos no pasan por los servidores del creador (a menos que el propio servidor llame a un servicio en línea).
El repo de GitHub cambió por última vez –, y la última versión (0.1.4) llegó al registro hace 7 meses.
Las apps compatibles con MCP, como Claude Desktop, Claude Code, Cursor y VS Code. También necesitas Node.js en tu computadora.
En la misma categoría: Spec Driven Development, Remote Desktop Commander, debuff
Servidores de la misma categoría hechos por otros creadores, ordenados por estrellas.
Cómo leer una tarjeta:★ Estrellas de GitHubiTres pilares: reseñas · revisiones · usoiActualizado = fecha en que se publicó la última versión en el registroi
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.
Let coding agents play, test and tune your 2D web game: live state, explained errors, replays, fuzz.
Copiado tal cual del repo del creador. PopNx MCP no lo ha revisado ni lo respalda. Se quitaron HTML, imágenes y scripts. Los enlaces llevan fuera de este sitio.
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.