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Adapter for exposing Command Registry commands as tools for AI models via MCP Proxy.

Project description

MCP Proxy Adapter

Adapter for integrating Command Registry with MCP Proxy, allowing you to use commands as tools for AI models.

Overview

MCP Proxy Adapter transforms commands registered in the Command Registry into a format compatible with MCP Proxy. This enables:

  1. Using existing commands as tools for AI models
  2. Creating a hybrid REST/JSON-RPC API for command execution
  3. Automatic generation of OpenAPI schemas optimized for MCP Proxy
  4. Managing tool metadata for better AI system integration

Installation

pip install mcp-proxy-adapter

Quick Start

from mcp_proxy_adapter import MCPProxyAdapter, CommandRegistry
from fastapi import FastAPI

# Create a command registry instance
registry = CommandRegistry()

# Register commands
@registry.command
def calculate_total(prices: list[float], discount: float = 0.0) -> float:
    """
    Calculates the total price with discount.
    Args:
        prices: List of item prices
        discount: Discount percentage (0-100)
    Returns:
        Total price with discount
    """
    subtotal = sum(prices)
    return subtotal * (1 - discount / 100)

# Create FastAPI app
app = FastAPI()

# Create and configure MCP Proxy adapter
adapter = MCPProxyAdapter(registry)

# Register endpoints in FastAPI app
adapter.register_endpoints(app)

# Generate and save MCP Proxy config
adapter.save_config_to_file("mcp_proxy_config.json")

Supported Request Formats

The adapter supports three request formats for command execution:

1. JSON-RPC format

{
  "jsonrpc": "2.0",
  "method": "command_name",
  "params": {
    "param1": "value1",
    "param2": "value2"
  },
  "id": 1
}

Example request to /cmd endpoint:

curl -X POST -H "Content-Type: application/json" -d '{
  "jsonrpc": "2.0",
  "method": "calculate_total",
  "params": {
    "prices": [100, 200, 300],
    "discount": 10
  },
  "id": 1
}' http://localhost:8000/cmd

Response:

{
  "jsonrpc": "2.0",
  "result": 540.0,
  "id": 1
}

2. MCP Proxy format

{
  "command": "command_name",
  "params": {
    "param1": "value1",
    "param2": "value2"
  }
}

Example request:

curl -X POST -H "Content-Type: application/json" -d '{
  "command": "calculate_total",
  "params": {
    "prices": [100, 200, 300],
    "discount": 10
  }
}' http://localhost:8000/cmd

Response:

{
  "result": 540.0
}

3. Params-only format

{
  "params": {
    "command": "command_name",
    "param1": "value1",
    "param2": "value2"
  }
}

or

{
  "params": {
    "query": "command_name",
    "param1": "value1",
    "param2": "value2"
  }
}

Example request:

curl -X POST -H "Content-Type: application/json" -d '{
  "params": {
    "command": "calculate_total",
    "prices": [100, 200, 300],
    "discount": 10
  }
}' http://localhost:8000/cmd

Response:

{
  "result": 540.0
}

Full Example: Integration with FastAPI

import logging
from fastapi import FastAPI, APIRouter
from mcp_proxy_adapter import CommandRegistry, MCPProxyAdapter, configure_logger

# Configure logging
logging.basicConfig(level=logging.INFO)
project_logger = logging.getLogger("my_project")

# Create FastAPI app
app = FastAPI(title="My API with MCP Proxy Integration")

# Create existing API router
router = APIRouter()

@router.get("/items")
async def get_items():
    """Returns a list of items."""
    return [
        {"id": 1, "name": "Smartphone X", "price": 999.99},
        {"id": 2, "name": "Laptop Y", "price": 1499.99},
    ]

app.include_router(router)

# Register commands
registry = CommandRegistry()

@registry.command
def get_discounted_price(price: float, discount: float = 0.0) -> float:
    """
    Returns the price after applying a discount.
    """
    return price * (1 - discount / 100)

# Create and register MCP Proxy adapter
adapter = MCPProxyAdapter(registry)
adapter.register_endpoints(app)

# Save MCP Proxy config
adapter.save_config_to_file("mcp_proxy_config.json")

Features

  • Universal JSON-RPC endpoint for command execution
  • Automatic OpenAPI schema generation and optimization for MCP Proxy
  • Tool metadata for AI models
  • Customizable endpoints and logging
  • Full test coverage and examples

License

MIT

Documentation

See docs/ for detailed guides, architecture, and examples.

📦 Примеры (examples/)

  • help_usage.py — базовое использование help-команды
  • help_best_practices.py — best practices для help
  • project_structure_example.py — структура проекта с MCPProxyAdapter
  • docstring_and_schema_example.py — как документировать команды для схемы
  • testing_example.py — как тестировать команды и интеграцию
  • extension_example.py — как расширять и кастомизировать команды и help

✅ Чеклист для добавления новой команды

  1. Реализовать функцию-команду с подробным docstring (EN)
  2. Добавить описание параметров (type, description, required)
  3. Добавить описание возврата (docstring, тип)
  4. Зарегистрировать команду в registry/dispatcher
  5. Добавить описание в get_commands_info (использовать docstring)
  6. Покрыть тестами (unit/integration, edge-cases, ошибки)
  7. Добавить пример использования в examples/
  8. Проверить интеграцию с help (и с параметром, и без)
  9. Проверить генерацию схемы/OpenAPI
  10. Документировать в README.md (EN/RU)

📦 Examples (EN)

  • help_usage.py — basic help command usage
  • help_best_practices.py — best practices for help
  • project_structure_example.py — project structure with MCPProxyAdapter
  • docstring_and_schema_example.py — how to document commands for schema
  • testing_example.py — how to test commands and integration
  • extension_example.py — how to extend/customize commands and help

✅ Checklist for adding a new command

  1. Implement the command function with detailed docstring (EN)
  2. Describe parameters (type, description, required)
  3. Describe return value (docstring, type)
  4. Register the command in registry/dispatcher
  5. Add description to get_commands_info (use docstring)
  6. Cover with tests (unit/integration, edge-cases, errors)
  7. Add usage example to examples/
  8. Check help integration (with/without param)
  9. Check schema/OpenAPI generation
  10. Document in README.md (EN/RU)

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