query-layer
MCP-сервер для Query Layer API
MCP-сервер (Model Context Protocol), который предоставляет AI-ассистентам API уровня запросов к метрикам. Создан на базе официального Python MCP SDK v2.
Быстрый старт
# Prerequisites: Python 3.10+, uv
uv sync
uv run mcp dev src/server.pyОткройте MCP Inspector по адресу, выведенному в консоль. Вы увидите доступный инструмент ping.
Related MCP server: prometheus-mcp
Интеграция с Cursor
Файл .cursor/mcp.json уже предварительно настроен. Перезапустите Cursor, и MCP-сервер query-layer станет доступен AI-ассистенту.
Локальная трассировка с Phoenix (необязательно)
# Terminal 1: start Phoenix
uv run phoenix serve
# Terminal 2: run the server pointing at Phoenix
export PHOENIX_COLLECTOR_ENDPOINT=http://localhost:6006
uv run mcp dev src/server.pyПросматривайте трейсы на http://localhost:6006 — Phoenix нативно отображает вызовы инструментов MCP, промпты и GenAI-спаны.
Документация
Документ | Назначение |
Постановка проблемы, подход к решению, план реализации | |
Ревью плана на предмет продакшн-готовности | |
Концепции MCP, технологические решения, проектные решения | |
Установка, настройка, запуск, конфигурация, устранение неполадок | |
Логирование, трассировка, OTLP, локальный Phoenix |
Структура проекта
src/
server.py # MCPServer + tools (entry point)
logging_config.py # Structured JSON logging to stderr
otel_config.py # OpenTelemetry exporter configuration
.cursor/
mcp.json # Cursor MCP server configuration
docs/
plan.md # Full implementation plan
review.md # Plan review
design.md # Design document
getting-started.md # Setup guide
observability.md # Observability guideЛицензия
Apache 2.0 — см. LICENSE.
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