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peterlozano

Datadog MCP Server

by peterlozano

list_events

Search and filter Datadog events like deploys, alerts, and comments by source, tags, priority, or time range to investigate incidents and track changes.

Instructions

Search Datadog events (deploys, alerts, comments, etc.) with filtering.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
toNoEnd time: relative or ISO 8601 or 'now'now
fromNoStart time: relative (1h, 1d, 7d) or ISO 86011d
tagsNoComma-separated tags to filter by
limitNoMax events to return
queryNoSearch query for events. E.g. 'sources:deploy', 'tags:env:prod'
cursorNoPagination cursor from previous response
sourceNoFilter by event source
priorityNoFilter by event priority

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

C2.9/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full behavioral burden. It implies a read-only search but never states that, nor does it mention pagination behavior, result caps (limit max 1000), default time window, or rate limits — all relevant for an event query tool.

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?

A single tight sentence with no wasted words, front-loading the action and resource. It is arguably too terse for an 8-parameter tool, but nothing in it is filler.

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 an 8-parameter query tool with no annotations and no output schema, the description is thin: it does not explain how query, tags, source, and priority interact, nor default behavior or pagination. The schema covers parameters, but the description leaves overall usage context incomplete.

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 all eight parameters (from/to/tags/limit/query/cursor/source/priority) are documented in the schema. The description adds no syntax or interaction detail, so the baseline 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?

States a specific verb and resource ('Search Datadog events') and clarifies scope with concrete examples (deploys, alerts, comments). It does not explicitly differentiate itself from siblings like search_logs or search_traces, but the resource is distinct enough to be actionable.

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 offers no when-to-use guidance, no prerequisites, and no mention of alternatives among the many siblings (search_logs, search_traces, list_metrics). 'With filtering' hints at use but leaves selection entirely to inference.

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