Google Cloud MCP Server

Query Logs

gcp-logging-query-logs

Query Google Cloud logs with custom Cloud Logging filters, searching text, JSON, and proto payloads plus metadata fields.

Instructions

Query Google Cloud Logs with custom filters. Searches across all payload types (text, JSON, proto) and metadata fields.

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": {
      "filter": "<filter>"
    },
    "name": "gcp-logging-query-logs"
  }
}

Input Schema

Name	Required	Description	Default
`limit`	No	Maximum number of log entries to return
`filter`	Yes	The filter to apply to logs (Cloud Logging query language)

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.5.0Sep 6, 2026

TDQS

B3.2/5.0

Behavior2/5

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

With no annotations, the description carries the full burden of behavioral disclosure. It mentions the search scope (text, JSON, proto payloads and metadata fields) but does not disclose read-only behavior, default time range, pagination, limits beyond the schema, or what the response contains.

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?

The description is two concise sentences with the core action front-loaded. Every sentence provides useful information and there is no redundant wording.

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?

For a tool with only two parameters and a fully documented schema, the description is mostly adequate. However, it lacks sibling differentiation and any statement about default time behavior, and with no output schema the agent is left uninformed about the return format.

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

Parameters4/5

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

Schema coverage is 100%, so the baseline is 3. The description adds value beyond the schema by clarifying that filters can target all payload types and metadata fields, which helps the agent understand the filter parameter's expressive scope.

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 action ('Query Google Cloud Logs with custom filters') and the resource, and adds useful scope detail about payload types and metadata fields. However, it does not explicitly distinguish itself from similar siblings like gcp-logging-query-time-range or gcp-logging-search-comprehensive.

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 explicit guidance on when to use this tool versus alternatives. 'Custom filters' implies a use case for users familiar with Cloud Logging query language, but there are no exclusions, prerequisites, or naming of sibling tools to route the agent.

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

Deploy Server