Greptimedb Mcp Server
Let your coding agent query GreptimeDB for metrics, logs, and traces while you debug production or tune observability pipelines.
Overview
GreptimeDB MCP server is a MCP server for the Operate phase that lets agents query and analyze GreptimeDB metrics, logs, and traces with SQL, TQL, and RANGE queries.
What is this MCP server?
- Run SQL queries against GreptimeDB over the MySQL protocol port (default 4002).
- Execute TQL and RANGE-style queries for time-series metrics exploration.
- Analyze logs and distributed traces alongside metrics in one agent session.
- Configure host, database, user, password, and session timezone via CLI args or env.
- Stdio MCP transport (PyPI package greptimedb-mcp-server v0.4.7).
- Server version 0.4.7 on PyPI (greptimedb-mcp-server)
- Default Greptime MySQL protocol port hint 4002
- Supports SQL, TQL, and RANGE query modes per catalog description
What problem does it solve?
Jumping between your agent, a SQL client, and observability UIs slows down debugging when Greptime holds the truth for metrics, logs, and traces.
Who is it for?
Solo builders or small teams already running GreptimeDB who want the agent to investigate telemetry during outages or performance regressions.
Skip if: Projects not using GreptimeDB, or builders who only need a one-off local demo without a reachable Greptime endpoint.
What do I get? / Deliverables
After you register the server, your agent can run Greptime queries in chat so you get tabled results and faster incident answers without leaving the IDE.
- Agent-executable SQL, TQL, and RANGE query results from your Greptime instance
- Repeatable MCP stdio configuration for host, port, credentials, and timezone
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Journey fit
Observability data belongs in the run-in-production phase when you need answers from live telemetry, not when you are still scoping an idea. SQL, TQL, and RANGE queries against metrics, logs, and traces are classic monitoring and incident-investigation workflows.
How it compares
Direct Greptime telemetry MCP integration, not a generic SQL skill or a hosted observability SaaS.
Common Questions / FAQ
Who is GreptimeDB MCP server for?
Developers and operators who use GreptimeDB for metrics, logs, or traces and want their AI coding agent to query that data programmatically.
When should I use GreptimeDB MCP server?
Use it during production monitoring, incident response, or performance tuning when you need SQL, TQL, or RANGE answers from live Greptime data.
How do I add GreptimeDB MCP server to my agent?
Install greptimedb-mcp-server from PyPI, add a stdio MCP entry with --host, --port, --database, --user, and --password (or equivalent env vars), then restart your MCP-capable agent.