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peterlozano

Datadog MCP Server

by peterlozano

search_logs

Search Datadog logs by service, status, host, environment, or raw query to retrieve timestamped entries, helping troubleshoot incidents and investigate issues quickly.

Instructions

Search Datadog logs with structured filters or raw query. Returns log entries with timestamp, service, status, host, and message.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
toNoEnd time: relative or ISO 8601 or 'now'now
envNoFilter by environment (e.g. prod, staging)
fromNoStart time: relative (15m, 1h, 1d, 7d) or ISO 860115m
hostNoFilter by host name
sortNoSort order (- prefix for descending)-timestamp
limitNoMax logs to return
queryNoRaw Datadog log query (overrides structured filters). E.g. 'service:web-api status:error'
cursorNoPagination cursor from previous response
sourceNoFilter by log source
statusNoFilter by log status/level
messageNoFree-text search in log message
serviceNoFilter by service name

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A3.5/5.0
Behavior3/5

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 helpfully enumerates the returned fields (timestamp, service, status, host, message), which compensates for the absent output schema, but omits pagination behavior (cursor), result defaults, and any rate-limit or auth context.

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 sentences, front-loaded with the action and result set, with zero filler. Every clause carries information.

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 12-parameter read tool with no annotations and no output schema, the description covers purpose and return fields but leaves pagination, default time-window behavior, and query-vs-filter precedence unexplained. Adequate but with clear gaps.

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 every parameter is already documented in the schema. The description adds no syntax or format details beyond that, so the baseline of 3 applies.

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 names a specific verb (Search) and resource (Datadog logs) and states the two supported modes (structured filters or raw query). It clearly distinguishes from siblings like search_traces and search_monitors, though it does not explicitly name them.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Usage is implied by the phrasing 'structured filters or raw query,' but there is no explicit when-to-use, when-not-to-use, or routing guidance versus sibling search tools. Notably, it does not clarify the precedence rule that a raw query overrides structured filters, which the schema alone mentions.

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