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Duck MCP Server

Duck MCP Server

by theddnc

Duck MCP Server šŸ¦†

A simple MCP (Model Context Protocol) server built with FastMCP.

Features

This server provides the following tools:

  • select_option: Ask user to select one option from provided choices (uses elicitation)

  • provide_information: Request additional information from user in natural language (uses elicitation)

  • request_manual_test: Request the user to perform manual testing and report results (uses elicitation)

Related MCP server: mcpbin

Installation

Prerequisites

  • Python 3.10 or higher

  • uv (recommended) or pip

Install Dependencies

Using uv (recommended):

uv sync

Using pip:

pip install -e .

Usage

Running the Server

# Run with default configuration from fastmcp.json
fastmcp run

# Or specify the config file explicitly
fastmcp run fastmcp.json

# Run with HTTP transport for testing
fastmcp run --transport http --port 8000

Using Python directly:

python server.py

Running with uv:

uv run fastmcp run server.py

Development Mode

Run with the FastMCP Inspector UI:

fastmcp dev

Inspect Server Capabilities

View all available tools, resources, and prompts:

fastmcp inspect

Installing to MCP Clients

Claude Desktop

fastmcp install claude-desktop

Cursor

fastmcp install cursor

Claude Code (VS Code Extension)

fastmcp install claude-code

Testing

You can test the server using a FastMCP client:

import asyncio
from fastmcp import Client

async def test_server():
    async with Client("http://localhost:8000/mcp") as client:
        # Ping the server to check connectivity
        await client.ping()
        print("Server is running!")

if __name__ == "__main__":
    asyncio.run(test_server())

Testing Elicitation Tools

The select_option, provide_information, and request_manual_test tools use FastMCP's elicitation feature to interactively request information from users:

import asyncio
from fastmcp import Client

async def elicitation_handler(message: str, response_type: type, params, context):
    """Handler that responds to server's elicitation requests"""
    print(f"Server asks: {message}")
    user_input = input("Your response: ")
    return response_type(selected_option=user_input) if hasattr(response_type, '__annotations__') and 'selected_option' in response_type.__annotations__ else response_type(information=user_input)

async def test_elicitation():
    async with Client("http://localhost:8000/mcp", elicitation_handler=elicitation_handler) as client:
        # Test select_option tool
        result = await client.call_tool("select_option", {
            "question": "What's your favorite programming language?",
            "options": ["Python", "JavaScript", "Rust", "Go"]
        })
        print(result.data)
        
        # Test provide_information tool
        result = await client.call_tool("provide_information", {
            "question": "What would you like to build today?"
        })
        print(result.data)
        
        # Test request_manual_test tool
        result = await client.call_tool("request_manual_test", {
            "test_description": "Navigate to the login page and verify the form renders correctly",
            "expected_outcome": "Login form should display username/password fields and submit button"
        })
        print(result.data)

if __name__ == "__main__":
    asyncio.run(test_elicitation())

Project Structure

duck-mcp/
ā”œā”€ā”€ server.py          # Main server implementation
ā”œā”€ā”€ fastmcp.json       # FastMCP configuration
ā”œā”€ā”€ pyproject.toml     # Project metadata and dependencies
ā”œā”€ā”€ README.md          # This file
└── tests/            # Test files (optional)

Development

Adding New Tools

To add a new tool to the server, simply decorate a function with @mcp.tool:

@mcp.tool
def my_new_tool(arg1: str, arg2: int) -> str:
    """Description of what this tool does"""
    # Your implementation here
    return "result"

Running Tests

pytest

Deployment

Local Deployment

The server runs with stdio transport by default, making it compatible with local MCP clients like Claude Desktop.

HTTP Deployment

For remote access, run with HTTP transport:

fastmcp run --transport http --host 0.0.0.0 --port 8000

FastMCP Cloud

Deploy to FastMCP Cloud for managed hosting (requires account):

fastmcp cloud deploy

Configuration

The fastmcp.json file contains the server configuration:

  • source: Location and entrypoint of the server code

  • environment: Python version and dependencies

  • deployment: Runtime configuration (transport, logging, etc.)

You can override any configuration via CLI arguments:

fastmcp run --port 8080 --log-level DEBUG

MCP Client Configuration

To use this MCP server with MCP-compatible clients (like Claude Desktop), add the following configuration to your client's mcp.json file:

{
  "mcpServers": {
    "duck-mcp": {
      "command": "uv",
      "args": ["run", "fastmcp", "run", "server.py"],
      "cwd": "/path/to/duck-mcp"
    }
  }
}

Using Python directly:

{
  "mcpServers": {
    "duck-mcp": {
      "command": "python",
      "args": ["server.py"],
      "cwd": "/path/to/duck-mcp"
    }
  }
}

Replace /path/to/duck-mcp with the actual path to your duck-mcp directory. The cwd (current working directory) ensures the server runs from the correct location.

Learn More

License

MIT

Available Tools

3 tools
provide_informationC

Request additional information from user in natural language.

Inputs: question (required). Returns: result

request_manual_testC

Request the user to perform manual testing and report results.

This tool allows an agent to ask a user to perform manual testing of functionality, and then collect the results via elicitation for analysis.

Inputs: test_description (required), expected_outcome. Returns: result

select_optionB

Ask user to select one option from provided choices.

Inputs: options (required), question (required). Returns: result

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

Loading tool schema changelog…

    TDQS

    B3.4/5.0

    Scored across 3 tools

    Disambiguation5/5

    Each tool has a distinct purpose: providing information, requesting manual tests, and selecting options. There is no overlap or ambiguity between them.

    Naming Consistency5/5

    All tool names follow a consistent verb_noun pattern (provide_information, request_manual_test, select_option), with clear and descriptive naming.

    Tool Count4/5

    With 3 tools, the set is minimal but well-scoped for a server focused on user interaction requests. It is slightly thin but appropriate for its apparent purpose.

    Completeness3/5

    The tools cover key user elicitation tasks (info, manual test, option selection), but lack general action requests or confirmations, leaving some gaps in the interaction surface.

    Maintenance

    ActivityInactive
    ResponsivenessOutdated data

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