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joyous-coder

universal-db-mcp

by joyous-coder

get_metrics

Retrieve server observability metrics as JSON. Choose summary, slow query history, or all categories to monitor performance and diagnose slow queries.

Instructions

Get server observability metrics. category=summary|slow_queries|all. Returns JSON.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
categoryNo返回的指标类别: summary(计数+直方图) / slow_queries(慢查询历史) / all(全部)summary

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv5.0.2

TDQS

B3.4/5.0
Behavior3/5

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

There are no annotations, so the description carries the burden of behavioral disclosure. 'Get' implies read-only behavior and 'Returns JSON' tells the caller the response format, but it does not disclose auth requirements, latency, or any operational caveats.

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

Conciseness5/5

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

Two short sentences, front-loaded with the core purpose, then a compact summary of the key parameter and return type. There is no filler or redundant explanation.

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

Completeness4/5

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

For a simple tool with one optional parameter and a rich schema, the description plus schema are sufficient to invoke it correctly. It could be more complete by explaining when to prefer this tool over sibling tools, but nothing essential is missing for a basic read-only metrics call.

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

Parameters3/5

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

Schema description coverage is 100% and the single parameter is fully documented with an enum, default value, and per-value meanings. The description only repeats the category values without adding meaning beyond what the schema already provides.

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?

Description uses a specific verb and resource: 'Get server observability metrics' and enumerates the categories. It clearly states what the tool returns, but it does not explicitly differentiate it from siblings like get_query_history or audit_log.

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 guidance is given on when to use get_metrics versus alternatives. The category list hints at use cases, but there is no explicit context, prerequisites, or exclusions to help an agent choose between this and related observability or query-history tools.

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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