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Grafana MCP Server
by nks1097

grafana_testar_fonte_dados

Tests connectivity and checks the health and integrity of a Grafana data source to confirm it is reachable and functioning before use.

Instructions

  1. Verificar conectividade e integridade de saúde de uma fonte de dados.

Input Schema

NameRequiredDescriptionDefault
uid_ou_idYes

Output Schema

NameRequiredDescriptionDefault
erroNoMensagem de erro amigável caso haja falha
dadosNoCarga útil da resposta estruturada
avisosNoLista de alertas e avisos operacionais
sucessoNoIndica se a operação foi bem-sucedida
metadadosNoMetadados da execução
id_requisicaoNoIdentificador único da operação

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

C2.8/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden. It does not say whether the test performs live network calls, how long it may take, what a failed vs. successful result looks like, or whether it changes any state — the only clue is the word 'verificar', which implies a non-mutating action but is not explicit.

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?

A single efficient sentence that front-loads the action. The leading '26.' is a list artifact that adds noise but does not impede comprehension.

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?

An output schema exists, so return-value explanation is unnecessary, and the tool surface is minimal (one parameter). However, the undocumented parameter and the absence of any disambiguation from sibling verification/diagnostic tools leave meaningful gaps for an agent choosing and invoking it.

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% and the single parameter 'uid_ou_id' has no description or title beyond its camel-cased name. The description does not clarify that this accepts either a datasource UID or numeric ID, nor where to obtain that identifier, so it fails to compensate for the schema gap.

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?

States a specific verb+resource combination ('verificar conectividade e integridade de saúde de uma fonte de dados'), which tells an agent this checks datasource health. It does not distinguish itself from closely related siblings like grafana_testar_conexao or grafana_diagnosticar_fontes_dados, leaving the agent to guess which of the three to call.

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 gives no conditions for when to use this versus grafana_testar_conexao, grafana_diagnosticar_fontes_dados, or grafana_obter_fonte_dados. No prerequisites, exclusions, or alternatives are mentioned.

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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