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winor30

mcp-server-datadog

by winor30

get_logs

Search and retrieve Datadog logs within a specified time range using a query string, with an optional limit on results. Use it to investigate incidents and monitor application events.

Instructions

Search and retrieve logs from Datadog

Input Schema

NameRequiredDescriptionDefault
toYesEnd time in epoch seconds
fromYesStart time in epoch seconds
limitNoMaximum number of logs to return. Default is 100.
queryNoDatadog logs query string

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.8.0

TDQS

B3.1/5.0
Behavior2/5

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

No annotations are provided, so the description must carry the behavioral burden, but it only implies a read operation through 'search and retrieve.' It does not disclose permissions, rate limits, pagination behavior, result handling, or whether the query is executed as a read-only Datadog search.

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 a single front-loaded sentence with no wasted words. It is efficient and easy to parse, even if it is terse.

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?

The tool is relatively simple and the schema fully documents parameters, but without annotations or an output schema the description should provide more behavioral context and usage guidance. It is minimally adequate for invoking the tool, but not complete for selecting it confidently among siblings.

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%, so the schema already explains all four parameters including time range, limit, and query string. The description adds no parameter-level meaning beyond what the schema provides, making the baseline score of 3 appropriate.

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 states a clear action and resource combination: 'Search and retrieve logs' from Datadog. It is specific enough to distinguish this from metrics- or trace-focused siblings, though it does not explicitly name or contrast those alternatives.

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 when-to-use guidance, prerequisites, or alternatives. An agent can infer this is for log retrieval, but there is no guidance on when to choose it over query_metrics, list_traces, or get_rum_events.

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