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GreptimeDB MCP Server

GreptimeDB MCP Server

Official
by GreptimeTeam
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

list_pipelines

List all data pipelines or retrieve details for a specific pipeline to inspect configurations and troubleshoot issues.

Instructions

List all pipelines or get details of a specific pipeline.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "list_pipelines"
  }
}

Input Schema

NameRequiredDescriptionDefault
nameNo

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.5.0

TDQS

C2.8/5.0
Behavior2/5

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

No annotations are present, so the description bears full responsibility. It only states the basic operation (list/details) but fails to disclose any behavioral traits such as rate limits, pagination, read-only nature, or what happens if the pipeline doesn't exist. The output schema exists but is not described.

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

Conciseness4/5

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

The description is concise with a single sentence that conveys the core functionality. It is front-loaded with the verb and resource, but could be more structured by separating the two modes explicitly.

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

Completeness3/5

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

Given the simple parameter and presence of an output schema, the description is minimally adequate. It covers the two use cases but lacks details about return structure, error handling, or behavioral constraints that would make it fully complete for an AI agent.

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?

With 0% schema description coverage, the description adds minimal value: it implies that providing a 'name' gives details, while omitting it lists all. However, it does not explain the format, constraints, or behavior of the parameter beyond what the schema already indicates.

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

Purpose4/5

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

The description clearly states the verb 'list' and resource 'pipelines', and indicates two modes: list all or get details of a specific pipeline. This is clearly distinct from sibling tools which operate on different resources like dashboards or SQL.

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?

The description does not provide any guidance on when to use this tool versus alternatives, nor does it mention prerequisites or when not to use it. This lack of context forces the AI to infer usage from the tool name alone.

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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