GreptimeDB

GreptimeDB is an open-source, cloud-native time-series database built for the Observability 2.0 era, unifying metrics, logs, and traces into a single data model and serving as a complete OpenTelemetry backend. It positions itself as a replacement for running Prometheus, Loki, and Elasticsearch as separate systems — instead providing one database that handles all three signal types with consistent query semantics and shared storage.

The GreptimeDB MCP Server is a particularly compelling feature for the AI agent ecosystem. It enables AI assistants and agents to securely access and manage GreptimeDB through structured MCP primitives — listing tables, reading data, and executing queries via SQL, TQL (PromQL-compatible), and RANGE queries. Built-in security features include read-only enforcement and data masking, ensuring AI agents can analyze observability data without risk of data modification or exposure. The server has been primarily developed for Claude Desktop but works with any MCP-compliant client.

Performance is a core strength: GreptimeDB optimizes for high write throughput (millions of data points per second), efficient compression for cost-effective long retention, and fast queries over time ranges for dashboards, alerts, and analytics. The team claims up to 50x cost reduction compared to traditional observability stacks, primarily through columnar storage on object storage (S3, GCS) with intelligent caching. GreptimeCloud offers managed hosting with a free tier, usage-based pricing, and tiered plans for teams and enterprises.

For DevOps teams, SREs, and platform engineers building AI-assisted operations workflows, GreptimeDB provides both the observability data store and the MCP bridge that lets AI agents reason about infrastructure health, query metrics, analyze log patterns, and correlate traces — all through natural language interactions.