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GreptimeDB MCP Server

GreptimeDB MCP Server

Official
by GreptimeTeam
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

execute_tql

Execute TQL queries for time-series analysis using standard PromQL syntax. Retrieve metrics and gain insights from GreptimeDB data.

Instructions

Execute TQL query for time-series analysis. TQL is PromQL-compatible - use standard PromQL syntax.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "query": "<query>",
      "start": "<start>",
      "end": "<end>",
      "step": "<step>"
    },
    "name": "execute_tql"
  }
}

Input Schema

NameRequiredDescriptionDefault
endYes
stepYes
queryYes
startYes
formatNojson
lookbackNo

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.5.0

TDQS

C2.9/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations provided, so the description must carry the full burden. It does not disclose whether the operation is read-only, destructive, or requires special permissions. No mention of side effects, rate limits, or response characteristics.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely short (two sentences) but front-loads the core purpose. However, it sacrifices critical details for brevity, resulting in below-average informativeness.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Despite having an output schema, the description omits key context: how to handle large result sets, error conditions, or time-series semantics. For a complex query tool, the description is insufficient.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, yet the description only explains the query syntax ('PromQL-compatible') without detailing parameters like start, end, step, lookback, or format. The agent cannot infer constraints or defaults from the description alone.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('Execute TQL query') and the domain ('time-series analysis'). It also mentions PromQL compatibility, distinguishing it from SQL queries (execute_sql) and other time-series tools (query_range).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No explicit guidance on when to use this tool versus alternatives like execute_sql or query_range. The mention of PromQL compatibility hints at syntax but does not provide decision criteria such as performance, authentication, or scope.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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