fastapitemplate MCP Server

A Model Context Protocol (MCP) server that exposes the fastapitemplate's tools to AI clients like Claude Desktop, VS Code, and other MCP-compatible applications.

Features

This MCP server provides comprehensive fastapitemplate's capabilities:

TODO: Add fastapitemplate's tools here

Installation

1. Install Python dependencies: bash cd fastapitemplate/mcp-server pip install -r requirements.txt

2. Run the server: bash python mcp_server.py

MCP Client Configuration

Claude Desktop

Add this configuration to your claude_desktop_config.json:

For a local STDIO connection:

{
  "mcpServers": {
    "fastapitemplate": {
      "command": "sh",
      "args": [
        "/absolute/path/to/fastapitemplate/mcp-server/run_mcp_server.sh"
      ],
      "env": {
        "GS_USER_ID": "xxxx",
        "GS_API_KEY": "xxxx"
      }
    }
  }
}

For a remote HTTP connection:

{
  "mcpServers": {
    "fastapitemplate": {
      "url": "http://localhost:8070/mcp",
      "headers": {
        "Authorization": "Bearer sk-gsu-..."
      }
    }
  }
}

VS Code MCP Extension

Add to your VS Code settings or .vscode/mcp.json:

For a local STDIO connection:

{
  "mcp": {
    "servers": {
      "fastapitemplate": {
        "command": "sh",
        "args": [
          "/absolute/path/to/fastapitemplate/mcp-server/run_mcp_server.sh"
        ],
        "env": {
          "GS_USER_ID": "xxxx",
          "GS_API_KEY": "xxxx"
        }
      }
    }
  }
}

For a remote HTTP connection:

{
  "mcp": {
    "servers": {
      "fastapitemplate": {
        "url": "http://localhost:8070/mcp",
        "headers": {
          "Authorization": "Bearer sk-gsu-..."
        }
      }
    }
  }
}

Usage Examples

Once connected to an MCP client, you can interact with the server using natural language:

Basic Operations

• TODO: Add fastapitemplate's tools here

Architecture

The server is built using: - FastMCP: Modern Python MCP framework for rapid development - Pydantic: Data validation and serialization - AsyncIO: Asynchronous operations for better performance

Data Models

• TODO: Add fastapitemplate's data models here

Mock Data

The server includes sample data for testing and demonstration: - TODO: Add fastapitemplate's sample data here

Development

Extending the Server

To add new tools, create functions decorated with @mcp.tool():

@mcp.tool()
async def my_new_tool(params: MyModel) -> Dict[str, Any]:
    """Description of what this tool does"""
    # Implementation
    return {"success": True, "data": result}

Adding Resources

To add new resources, use the @mcp.resource() decorator:

@mcp.resource("mydata://endpoint")
async def my_resource() -> str:
    """Get my data as a resource"""
    data = await get_my_data()
    return json.dumps(data, indent=2)

Integration with fastapitemplate

This MCP server is based on the fastapitemplate's AI tools: - ai_gpt_fn_app.py: Core fastapitemplate tools

It provides the same functionality but exposed through the standardized MCP protocol, making it accessible to any MCP-compatible AI client.

Transport Modes

Currently supports: - HTTP: HTTP/SSE transport for remote clients (default) - STDIO: Standard input/output for local clients

Logging

The server provides detailed logging for debugging and monitoring: - Tool invocations and parameters - Data validation errors - Mock database operations - Performance metrics

License

This MCP server follows the same license as the fastapitemplate project.