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krzko

Google Cloud MCP Server

by krzko

Comprehensive Log Search

gcp-logging-search-comprehensive

Search across all Google Cloud log fields including payloads, labels, HTTP requests, and metadata. Filter by time range, severity, resource, and result limit to retrieve detailed log entries.

Instructions

Search across all log fields including textPayload, jsonPayload, protoPayload, labels, HTTP requests, and metadata. Provides maximum context.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
searchTermYesTerm to search for across all payload types and fields
timeRangeNoTime range to search (e.g., "1h", "24h", "7d")1h
severityNoMinimum severity level to filter by
resourceNoResource type to filter by (e.g., "cloud_function", "gke_container")
limitNoMaximum number of log entries to return
Behavior2/5

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

With no annotations provided, the description carries the full burden of disclosing behavioral traits. It only states that the tool 'provides maximum context' but does not mention read-only nature, authentication requirements, rate limits, or response format. The behavioral impact is largely unspecified.

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 two sentences long and front-loads key information about searched fields. The second sentence is somewhat generic ('Provides maximum context') but not overly verbose. It earns its place but could be tighter.

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?

Given the tool has 5 parameters and no output schema, the description is incomplete. It fails to explain return values, pagination behavior, error handling, or how 'maximum context' manifests. Without annotations, this gap leaves the agent guessing about the tool's full behavior.

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 coverage is 100%, so the input schema already documents all parameters thoroughly. The description adds minimal value beyond the schema—only listing some payload fields in prose. It does not explain parameter interactions or provide examples, warranting a baseline score of 3.

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 tool's purpose: searching across all log fields including specific types like textPayload and jsonPayload. It uses a specific verb ('search') and resource ('logs'), making the purpose clear. However, it does not explicitly distinguish itself from sibling tools like gcp-logging-query-logs, which might have narrower scope.

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 provides no guidance on when to use this tool versus alternatives (e.g., gcp-logging-query-logs for simpler queries). There is no mention of prerequisites, exclusions, or typical use cases, leaving the agent without direction for tool selection.

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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