AI Tools and Skills

SigNoz launched two integration options for AI coding assistants, an MCP Server and Agent Skills, enabling developers to query observability data using natural language and automate tasks like log analysis and root cause identification. The MCP Server connects tools like Claude and Cursor directly to SigNoz instances, while Agent Skills provide markdown-based guides for agents to perform specialized observability workflows. These integrations aim to simplify monitoring and debugging by allowing developers to interact with telemetry data through conversational AI.

SigNoz provides two ways to connect AI coding assistants to your observability data, allowing you to seamlessly set up SigNoz, write optimized queries, or analyze your telemetry: Integration Options MCP Server The SigNoz MCP Server https://github.com/SigNoz/signoz-mcp-server implements the Model Context Protocol MCP , enabling direct communication between AI assistants and your SigNoz instance. - Query metrics, logs, and traces using natural language - Inspect alerts, dashboards, and services - Works with Claude, Cursor, Gemini, Codex, etc. Get started with the MCP Server → https://signoz.io/docs/ai/signoz-mcp-server Agent Skills SigNoz Agent Skills https://github.com/SigNoz/agent-skills are an open format for extending AI coding assistants with specialized knowledge about SigNoz. Skills are markdown files SKILL.md that guide agents to perform observability tasks. - Explore SigNoz documentation and ClickHouse query patterns - Works with Claude Code and skills.sh compatible agents like Codex, Cursor, Gemini, OpenCode, etc. - Install with a single command Get started with Agent Skills → https://signoz.io/docs/ai/agent-skills MCP Use Cases Once you have the MCP server connected, explore practical workflows: - Search and analyze logs by asking questions in plain English. - Ask "why is this slow?" and get a span breakdown with the bottleneck identified. - Paste a trace ID and reconstruct the full request path with root cause analysis.