Product Management MCP Server
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Product Management MCP Servershow me all products in the Electronics category"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
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
Related MCP server: E-commerce MCP Server
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.txtMCP инструменты
В mcp_server/server.py реализованы tools:
list_products(category: str | None = None)get_product(product_id: int)add_product(name: str, price: float, category: str, in_stock: bool = True)get_statistics()
Особенности:
transport:
stdioдекораторы
@mcp.tooltype hints + docstrings
ValueError, если товар не найден
Агентный flow (LangGraph)
Узел
analyze: mock LLM (rule-based) разбирает запрос и формируетaction + params.Узел
execute: вызывает MCP tools через stdio-клиент + custom tools.Узел
respond: формирует финальный текст пользователю.
Custom tools:
calculate_discountформаттеры ответа (
format_products,format_statistics)
API
POST /api/v1/agent/queryGET /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 --buildAPI 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 8000Тесты
pytest -qПокрытие 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 ЭлектроникаКакая средняя цена продуктов?Добавь новый продукт: Мышка, цена 1500, категория ЭлектроникаПосчитай скидку 15% на товар с ID 1
This server cannot be deployed
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