Gigapipe

Integrates with Gigapipe's observability platform to query Prometheus metrics with PromQL, search Loki logs with LogQL, and retrieve Tempo traces by ID through unified HTTP/HTTPS access with optional authentication.

This MCP server provides unified access to Gigapipe's observability platform, enabling AI assistants to query Prometheus metrics with PromQL, search Loki logs with LogQL, and retrieve Tempo traces by ID through a single interface. Built in Go using the mcp-go library, it connects to Gigapipe instances via HTTP/HTTPS with optional basic authentication, offering tools for metric queries with time ranges and step intervals, log searches with configurable limits, trace retrieval in JSON format, and label/tag discovery across all three data sources. The implementation includes cross-platform binary releases for Linux, macOS, and Windows, making it valuable for DevOps teams monitoring distributed systems, SRE workflows requiring correlation between metrics, logs, and traces, and automated troubleshooting scenarios that need to query multiple observability data types through a unified API.