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cli2mcp

by RonieNeubauerversion 0.1.4i★ –iRuns on your computer
Registry nameio.github.RonieNeubauer/cli2mcp

Install

Overview

Description from the maker (original English)

Wrap any CLI as a Model Context Protocol server - schema auto-inferred from --help.

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

  • Connection: Runs on your computer
  • Transport: stdio
  • Category: Other

Install

Pick the AI app you use, then copy the settings.

Before you install

  • Basic checks: 1 of 1 passed
  • Runs on your computer with your user’s permissions (files, network, apps).
  • The registry lists no key to fill in.

You need

  • npmNode.js installed (for the npx command)

Which app do you use?

Pick your app above. We remember it, so next time the button says “Install in …”.

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

{
  "mcpServers": {
    "cli2mcp": {
      "command": "npx",
      "args": [
        "-y",
        "cli2mcp"
      ]
    }
  }
}

Run this in your terminal

claude mcp add cli2mcp -- npx -y cli2mcp

This one needs values on its command line, so copy the settings and fill them in.

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "cli2mcp": {
      "command": "npx",
      "args": [
        "-y",
        "cli2mcp"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This one needs values on its command line, so copy the settings and fill them in.

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "cli2mcp": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "cli2mcp"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.

Your choice stays on this device in a cookie; no account needed.

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 6, 2026

  • ✓ Pass

    Maker matches the repo

    The registry name was verified with the GitHub account RonieNeubauer, which owns the repo

  • … Not checked yet

    Still maintained

    We have not read this repo from GitHub yet

  • … Not checked yet

    Has a licence

    We have not read this repo from GitHub yet

  • – Not applicable

    Endpoint responds

    This one runs on your computer; there is no internet endpoint

  • – Not applicable

    Sign-in with OAuth

    Runs on your computer and uses local settings instead

  • … Not checked yet

    No hidden instructions in tool descriptions

    Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Otheri

  • More stars than 0% of the other 32505 servers in this category
  • Published to the registry more recently than 7% of the other 32505 servers in this category
  • Basic checks equal to or better than 100% of the other 32505 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is cli2mcp safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

The registry does not list a required key, though some servers ask you to sign in on first use.

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed –, and the latest version (0.1.4) reached the registry 7 months ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Node.js on your computer.

What can I use instead?

In the same category: Spec Driven Development, Remote Desktop Commander, topo^alpin

Alternatives

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Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

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Runs on your computer★ 440MITUpdated 14 months ago
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Remote Desktop Commander

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Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.

Runs in the cloud★ 211Updated yesterday
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topo^alpin

by topoalpin.app

Avalanche bulletins and mountain weather forecasts for any place in the Alps.

Runs in the cloudUpdated today
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README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

cli2mcp

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>

Why

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.


Install

npm install -g cli2mcp

or invoke without installing

npx cli2mcp

Requires Node.js 22+.


Configure your MCP client

cli2mcp is launched by your client as a stdio subprocess. Add an entry per CLI you want to expose.

Claude Desktop

Config file location:

OSPath
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.

Other clients
ClientConfig fileFormat
ChatGPT (OpenAI Agents SDK)MCPServerStdio parameter — see OpenAI Agents docscommand: "npx", args: ["-y", "cli2mcp", " "]
Cursor.cursor/mcp.json (project) or ~/.cursor/mcp.json (global)Same mcpServers block as above
ClineVS Code → Cline → MCP Settings → cline_mcp_settings.jsonSame mcpServers block
Windsurf~/.codeium/windsurf/mcp_config.jsonSame mcpServers block
Gemini CLI~/.gemini/settings.jsonSame mcpServers block
Continue~/.continue/config.json → experimental.modelContextProtocolServersSame launcher
Zed~/.config/zed/settings.json → context_serversSame launcher
Any stdio-capable MCP clientper the client's docsSame 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.


Quick wins — copy-paste configs

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. cli2mcp does not install them for you.


How it compares

ApproachLOC per CLINew flag handlingMaintenance
Hand-written MCP server (TypeScript SDK)~80–150manual schema editper-CLI release cycle
OpenAPI → MCP generatorsn/arequires an OpenAPI specdoes not cover arbitrary CLIs
Wrapping bash / sh as a tool~10n/a — gives the AI a shellunsafe, no schema, no sandbox
`cli2mcp `0automatic at next startnone — 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.


Verified targets

These CLIs are covered by the test suite or have been manually exercised end-to-end:

CLIStatusNotes
jq✅ testedhelp-on-stderr correctly captured; stdin piping works
ripgrep (rg)✅ tested90+ flags inferred; args positional handled
curl✅ fixtureshape extraction validated against bundled fixture
node✅ integration testend-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.


How --help becomes a JSON Schema

Help fragmentMCP property
--flagboolean
--flag / / string
--flag / / number
--flag string enum with choices
Repeatable flagarray
Positional argsargs: array
Reserved input stdinstring 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.


Options

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

Piping stdin

Reserved input property stdin is piped to the subprocess:

{ "args": [".name"], "stdin": "{\"name\": \"cli2mcp\"}" }

How it works

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).


Security

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:

  • Only expose CLIs whose blast radius you accept. jq, rg, pandoc are mostly safe (read-only, deterministic). curl, ffmpeg --output, sqlite3, rm, kubectl, aws are not.
  • The AI is not sandboxed. A prompt injection attack could cause an exposed curl to fetch evil.example.com, an exposed rm to delete files, etc.
  • Use `--cwd` to constrain filesystem scope when wrapping CLIs that touch files.
  • Use `--env` deliberately. Do not pass through credentials the model shouldn't reach.
  • Never expose `sh`, `bash`, `zsh`, `python -c`, or anything with eval semantics — that bypasses every safeguard 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.


Troubleshooting

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.


Contributing

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


Star history

If cli2mcp saved you an afternoon of writing MCP boilerplate, a star helps other people find it.


Author

Built by Ronie Neubauer — Principal Engineer, 22+ years shipping production systems.


License

MIT © 2026 Ronie Neubauer.

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