MCP UseCase Function Server

MCP UseCase Function Server

Triggers predefined functions based on specific usecases including data analysis, text processing, mathematical calculations, file operations, and web request simulations through natural language prompts.

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README

MCP UseCase Function Server

A Model Context Protocol (MCP) server that triggers functions based on specific usecases, built with Python and FastMCP.

Features

  • UseCase-based Function Triggering: Execute functions based on predefined usecases
  • stdio Transport: Compatible with Claude Desktop
  • Multiple Function Types: Data analysis, text processing, calculations, file operations, and web requests
  • Easy Integration: Simple setup for Claude Desktop

Available Usecases

  1. data_analysis - Analyze numerical data (mean, max, min, count)
  2. text_processing - Process text (uppercase, lowercase, word count, char count)
  3. calculation - Mathematical operations (add, multiply, divide)
  4. file_operation - File handling operations (info, simulation)
  5. web_request - Web request simulation (GET, POST, etc.)

Installation

  1. Install dependencies:
python3 -m pip install -r requirements.txt
  1. Test the server:
python3 test_client.py

Claude Desktop Integration

Add this configuration to your Claude Desktop settings:

macOS

Edit: ~/Library/Application Support/Claude/claude_desktop_config.json

Windows

Edit: %APPDATA%/Claude/claude_desktop_config.json

Linux

Edit: ~/.config/claude/claude_desktop_config.json

Add the server configuration:

{
  "mcpServers": {
    "usecase-function-server": {
      "command": "python3",
      "args": ["/path/to/your/mcp_server.py"],
      "env": {}
    }
  }
}

Replace /path/to/your/mcp_server.py with the actual path to your server file.

Usage

Available Tools

  1. trigger_function_by_usecase(usecase, parameters)

    • Execute a function based on usecase
    • Returns result with success status
  2. list_available_usecases()

    • Get all available usecases
    • Returns array of usecase names
  3. get_usecase_info(usecase)

    • Get information about a specific usecase
    • Returns usecase details and function description

Example Usage in Claude

Can you analyze this data using the data_analysis usecase: [1, 2, 3, 4, 5]
Please convert "hello world" to uppercase using text_processing
Calculate the sum of 10, 20, and 30 using the calculation usecase

Deployment

For production deployment:

  1. Docker Deployment (Recommended):
FROM python:3.11-slim
WORKDIR /app
COPY requirements.txt .
RUN pip install -r requirements.txt
COPY mcp_server.py .
CMD ["python3", "mcp_server.py"]
  1. System Service:
# Run as a service
python3 mcp_server.py
  1. Cloud Platforms:
    • Deploy to AWS Lambda, Google Cloud Functions, or Azure Functions
    • Modify transport from stdio to HTTP for web-based deployments

Development

Adding New Usecases

  1. Add to usecase_functions dictionary in mcp_server.py
  2. Create the corresponding function
  3. Test with the test client

Custom Functions

Implement new functions following this pattern:

def your_custom_function(parameters: Dict[str, Any]) -> Dict[str, Any]:
    """Your function description"""
    # Process parameters
    # Return result dictionary
    pass

Troubleshooting

  1. Import Errors: Ensure all dependencies are installed
  2. Path Issues: Use absolute paths in Claude Desktop config
  3. Permission Issues: Make sure the script is executable
  4. Connection Issues: Verify the server starts without errors

Files

  • mcp_server.py - Main MCP server implementation
  • test_client.py - Test client for validation
  • requirements.txt - Python dependencies
  • claude_desktop_config.json - Example Claude Desktop configuration# mcp-server-test

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