M
MCP Directory CURATED DIRECTORY
911 MCP servers indexed
中文
← Back to directory
COMPARE UP TO 4 SERVERS

Compare MCP servers

Compare scores, permissions, risks, and fit in one decision-focused table.

DimensionGreptimeDB MCP ServerQuery and analyze GreptimeDB metrics, logs, and traces via SQL, TQL, and RANGE queries.MCP Toolbox for DatabasesGoogle's official database MCP toolbox — define AI-accessible database tools via config
FMRS60 / 100 · C74 / 100 · B
Reliability10 / 2013 / 20
Security and permissions12 / 2013 / 20
Maintenance11 / 2017 / 20
Documentation14 / 2016 / 20
Setup experience13 / 2015 / 20
Best for
  • Developers working with time-series and observability data.
  • Teams needing natural language access to their database for query and analysis.
  • Users wanting to integrate AI-assisted data exploration within MCP clients.
  • Teams that want precise control over which database operations an AI can perform, rather than open arbitrary SQL execution
  • Scenarios needing a unified MCP setup across multiple database engines
Not for
  • Users who need write operations or DDL/DML (read-only by default; write mode only for local/test, extremely risky).
  • Users not using GreptimeDB.
  • Users who need direct database access without MCP integration.
  • Lightweight cases that just want to run a few ad-hoc SQL queries without maintaining a tools.yaml config (a simpler single-database MCP may be a better fit)
Required permissions
  • Read-only access to GreptimeDB for SQL, TQL, and RANGE queries.
  • Access to HTTP API (default port 4000) for pipeline and dashboard management.
  • Access to configured credentials via environment variables or CLI arguments.
  • Data masking is enabled by default to prevent sensitive column exposure.
  • Database credentials (username/password/connection string) are supplied via env vars or config
  • A tool's actual permission is whatever SQL statement is defined in tools.yaml — designed for least privilege, but misconfiguration can still over-expose access
Risks and side effects
  • If write mode is enabled (disabled by default), AI could execute destructive SQL; never enable against production.
  • Queries may be expensive if complex or misused; restrict access and resources.
  • Providing secret environment variables over HTTP could increase exposure risk.
  • Database may be inaccessible due to network configuration or startup issues.
  • If tools.yaml defines SQL statements that allow unconstrained writes or deletes, the AI could accidentally modify data
  • The prebuilt toolsets (--prebuilt) favor convenience and may expose broader query capability than a specific business actually needs — use a custom tools.yaml in production
Supported clientsClaude DesktopClaude Code, Gemini CLI, Zed, Antigravity
Tools130