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datadog-mcp-server

search-logs

Search Datadog logs by query with time range filtering. Filter by service, status, or custom fields, control sort order, and limit results.

Instructions

Search Datadog logs by query with time range filtering

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesDatadog log query. Example: service:web-api status:error @http.status_code:[500 TO 599]
fromYesStart time (ISO 8601). Example: 2026-02-26T00:00:00Z
toYesEnd time (ISO 8601). Example: 2026-02-26T23:59:59Z
limitNoMax results (default 50, max 1000)
sortNoSort order: -timestamp (newest first) or timestamp (oldest first)-timestamp
indexesNoLog indexes to search. Example: ["main"]
extractFieldsNoComma-separated dotted paths to project from response (e.g. 'id,name,owner.name,columns.*.name'). Use `*` as wildcard for arrays/objects. Wrap field names with dots in backticks. Reduces response tokens dramatically on large entities.
Behavior2/5

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

No annotations provided, so description must disclose behaviors. It only states the basic search action with time range filtering. Missing details like read-only nature, authentication needs, rate limits, pagination behavior, or response format. The limit parameter hints at pagination but not described.

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 sentence of 8 words is very concise. While it lacks structured elements like bullet points, it efficiently communicates the core purpose without extraneous content.

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?

For a tool with 7 parameters (3 required), no output schema, and no annotations, the description is too minimal. It doesn't cover expected return values, pagination, or usage examples. The schema covers parameter details but the overall context of using the tool is 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%, and the description adds no additional parameter context. Baseline 3 is appropriate since the schema already documents all parameters meaningfully.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description 'Search Datadog logs by query with time range filtering' clearly states the verb ('search'), resource ('Datadog logs'), and scope ('query with time range filtering'). It distinguishes from sibling tools like search-audit-logs or search-ci-pipelines by specifying logs.

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?

No explicit guidance on when to use this vs alternatives. The description implies use for log search but doesn't mention when to avoid or what other tools might be better for specific log types or filtering needs.

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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