Skip to main content

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)

Project details


Release history Release notifications | RSS feed

This version

2.1.0

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

mcp_proxy_adapter-2.1.0.tar.gz (114.6 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

mcp_proxy_adapter-2.1.0-py3-none-any.whl (39.0 kB view details)

Uploaded Python 3

File details

Details for the file mcp_proxy_adapter-2.1.0.tar.gz.

File metadata

  • Download URL: mcp_proxy_adapter-2.1.0.tar.gz
  • Upload date:
  • Size: 114.6 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.12.3

File hashes

Hashes for mcp_proxy_adapter-2.1.0.tar.gz
Algorithm Hash digest
SHA256 78c7b851d259f55c72bbb298547df5552382755b58da343727a0aeaef878c78b
MD5 ee9a7c72e85b2c261c482bf12efe15b7
BLAKE2b-256 152c1f4a708d1bdbf58706840862b056e3448d054b03c8edc2d3e6098faf4ff8

See more details on using hashes here.

File details

Details for the file mcp_proxy_adapter-2.1.0-py3-none-any.whl.

File metadata

File hashes

Hashes for mcp_proxy_adapter-2.1.0-py3-none-any.whl
Algorithm Hash digest
SHA256 c78b34d6e2c2eb46fc62deb25221268d9b7a91ce08ee3bb91e560f1b1d81749a
MD5 902a170a6eb74a4f0773d534a6d939c1
BLAKE2b-256 5b85c0737c4cedeb9f3e758d95ebc9ea14c550d2b4e49056ba03ae8476341c59

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page