VictoriaMetrics/mcp-victoriametrics
🔌 MCP ServerVictoriaMetrics
Connect your AI agents directly to VictoriaMetrics data using the Model Context Protocol for seamless observability insights.
The VictoriaMetrics MCP Server acts as a bridge between AI-powered assistants and your observability stack. By leveraging the Model Context Protocol, it allows LLMs to query VictoriaMetrics instances securely and efficiently. This implementation is written in Go, ensuring high performance and reliability when handling complex time-series data requests. Key features include the ability to fetch metrics, execute PromQL/MetricsQL queries, and retrieve system health data directly within an AI agent's workflow. This tool is essential for teams looking to build 'AI-Ops' capabilities, where the AI can proactively diagnose infrastructure issues, explain alert spikes, or provide summary reports based on real-time telemetry. By standardizing the communication via MCP, it ensures compatibility with various MCP-compliant AI clients, making it a versatile addition to any DevOps or SRE toolkit focused on AI-driven observability.
💡Highlights
- ├─Native MCP protocol implementation
- ├─Real-time MetricsQL query support
- └─Go-based high-performance server
🎯For
- ├─DevOps Engineers
- ├─SREs
- └─AI Application Developers