Product Management MCP Server

Product Management MCP Server

Provides tools for managing a product catalog, including functions to list, add, and retrieve product statistics. It enables AI agents to perform inventory operations and data analysis through a standardized interface.

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README

AI Engineer Test Task

Реализация тестового задания:

  • MCP сервер на FastMCP (stdio, 4 инструмента)
  • LangGraph агент с mock LLM и custom tools
  • FastAPI endpoint для общения с агентом
  • Dockerfile + docker-compose
  • Набор тестов (3+)

Стек

  • Python 3.11+
  • FastMCP
  • MCP Python SDK
  • LangGraph + langchain-core
  • FastAPI + Uvicorn
  • Pytest

Структура проекта

.
├── app
│   ├── agent
│   │   ├── graph.py
│   │   ├── mcp_client.py
│   │   ├── mock_llm.py
│   │   └── tools.py
│   ├── main.py
│   └── schemas.py
├── mcp_server
│   ├── data/products.json
│   └── server.py
├── tests
│   ├── test_agent.py
│   ├── test_api.py
│   └── test_mcp_server.py
├── Dockerfile
├── docker-compose.yml
└── requirements.txt

MCP инструменты

В mcp_server/server.py реализованы tools:

  1. list_products(category: str | None = None)
  2. get_product(product_id: int)
  3. add_product(name: str, price: float, category: str, in_stock: bool = True)
  4. get_statistics()

Особенности:

  • transport: stdio
  • декораторы @mcp.tool
  • type hints + docstrings
  • ValueError, если товар не найден

Агентный flow (LangGraph)

  1. Узел analyze: mock LLM (rule-based) разбирает запрос и формирует action + params.
  2. Узел execute: вызывает MCP tools через stdio-клиент + custom tools.
  3. Узел respond: формирует финальный текст пользователю.

Custom tools:

  • calculate_discount
  • форматтеры ответа (format_products, format_statistics)

API

  • POST /api/v1/agent/query
  • GET /health

Пример запроса:

curl -X POST "http://localhost:8000/api/v1/agent/query" \
  -H "Content-Type: application/json" \
  -d '{"query":"Покажи все продукты в категории Электроника"}'

Запуск

Вариант 1: Docker Compose (рекомендуется)

docker compose up --build

API будет доступен на http://localhost:8000.

Вариант 2: Локально

python3 -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt
uvicorn app.main:app --reload --port 8000

Тесты

pytest -q

Покрытие требований тестами:

  • tests/test_mcp_server.py:
    • добавление продукта
    • статистика
    • обработка ошибки ValueError
  • tests/test_agent.py:
    • вычисление средней цены
    • расчет скидки через custom tool
  • tests/test_api.py:
    • проверка POST /api/v1/agent/query

Примеры запросов к агенту

  • Покажи все продукты в категории Электроника
  • Какая средняя цена продуктов?
  • Добавь новый продукт: Мышка, цена 1500, категория Электроника
  • Посчитай скидку 15% на товар с ID 1

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