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CLI

# Generate CLI

Scaffold a standalone typed CLI from any MCP server

New in version `3.0.0` `fastmcp list` and `fastmcp call` are general-purpose — you always specify the server, the tool name, and the arguments from scratch. `fastmcp generate-cli` goes further: it connects to a server, reads its tool schemas, and writes a standalone Python script where every tool is a proper subcommand with typed flags, help text, and tab completion. The result is a CLI that feels hand-written for that specific server. MCP tool schemas already contain everything a CLI framework needs — parameter names, types, descriptions, required/optional status, and defaults. `generate-cli` maps that into cyclopts commands, so JSON Schema types become Python type annotations, descriptions become `--help` text, and required parameters become mandatory flags.

##
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Generating a Script

Point the command at any server target and it writes a CLI script:

    fastmcp generate-cli weather
    fastmcp generate-cli http://localhost:8000/mcp
    fastmcp generate-cli server.py my_weather_cli.py

The second positional argument sets the output path (defaults to `cli.py`). If the file already exists, pass `-f` to overwrite:

    fastmcp generate-cli weather -f

##
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What You Get

The generated script is a regular Python file — executable, editable, and yours:

    $ python cli.py call-tool --help
    Usage: weather-cli call-tool COMMAND

    Call a tool on the server

    Commands:
      get_forecast  Get the weather forecast for a city.
      search_city   Search for a city by name.

Each tool has typed parameters with help text pulled directly from the server’s schema:

    $ python cli.py call-tool get_forecast --help
    Usage: weather-cli call-tool get_forecast [OPTIONS]

    Get the weather forecast for a city.

    Options:
      --city    [str]  City name (required)
      --days    [int]  Number of forecast days (default: 3)

Beyond tool commands, the script includes generic MCP operations — `list-tools`, `list-resources`, `read-resource`, `list-prompts`, and `get-prompt` — that always reflect the server’s current state, even if tools have changed since generation.

##
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Parameter Handling

Parameters are mapped based on their JSON Schema type: Simple types (`string`, `integer`, `number`, `boolean`) become typed flags:

    python cli.py call-tool get_forecast --city London --days 3

Arrays of simple types become repeatable flags:

    python cli.py call-tool tag_items --tags python --tags fastapi --tags mcp

Complex types (objects, nested arrays, unions) accept JSON strings. The `--help` output shows the full schema so you know what structure to pass:

    python cli.py call-tool create_user \
      --name John \
      --metadata '{"role": "admin", "dept": "engineering"}'

##
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Agent Skill

Alongside the CLI script, `generate-cli` writes a `SKILL.md` file — a Claude Code agent skill that documents every tool’s exact invocation syntax, parameter flags, types, and descriptions. An agent can pick up the CLI immediately without running `--help` or experimenting with flag names. To skip skill generation:

    fastmcp generate-cli weather --no-skill

##
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How It Works

The generated script is a client, not a server — it connects to the server on every invocation rather than bundling it. A `CLIENT_SPEC` variable at the top holds the resolved transport (a URL string or `StdioTransport` with baked-in command and arguments). The most common edit is changing `CLIENT_SPEC` — for example, pointing a script generated from a dev server at production. Beyond that, the helper functions (`_call_tool`, `_print_tool_result`) are thin wrappers around `fastmcp.Client` that are easy to adapt. The script requires `fastmcp` as a dependency. If it lives outside a project that already has FastMCP installed:

    uv run --with fastmcp python cli.py call-tool get_forecast --city London

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