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TANTIOPE

Datadog MCP Server

traces

Search, aggregate, and filter APM traces to debug request flow and latency issues. Use duration, HTTP status, and error filters for precise analysis.

Instructions

Analyze APM traces for request flow and latency debugging. Actions: search (find spans), aggregate (group stats), services (list APM services). Key filters: minDuration/maxDuration ("500ms", "2s"), httpStatus ("5xx", ">=400"), status (ok/error), errorMessage (grep). APM METRICS: Traces auto-generate metrics in trace..* namespace (e.g. trace.express.request). Use metrics tool to query: avg:trace.express.request.duration{service:my-service}. For percentiles (p95), use the root metric WITHOUT .duration suffix: p95:trace.express.request{service:my-service}

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
actionYesAction to perform
queryNoAPM trace search query (Datadog syntax). Example: "@http.status_code:500", "service:my-service status:error"
fromNoStart time. Formats: ISO 8601, relative (30s, 15m, 2h, 7d), precise (3d@11:45:23, yesterday@14:00)
toNoEnd time. Same formats as "from". Example: from="3d@11:45" to="3d@12:55"
serviceNoFilter by service name. Example: "my-service", "postgres"
operationNoFilter by operation name. Example: "express.request", "mongodb.query"
resourceNoFilter by resource name (endpoint/query). Supports wildcards. Example: "GET /api/*", "*orders*"
statusNoFilter by span status - "ok" for successful, "error" for failed spans
envNoFilter by environment. Example: "production", "staging"
minDurationNoMinimum span duration (find slow spans). Examples: "1s", "500ms", "100ms"
maxDurationNoMaximum span duration. Examples: "5s", "1000ms"
httpStatusNoHTTP status code filter. Examples: "500", "5xx" (500-599), "4xx" (400-499), ">=400"
errorTypeNoFilter by error type (grep-like). Example: "TimeoutError", "ConnectionRefused"
errorMessageNoFilter by error message (grep-like). Example: "timeout", "connection refused"
limitNoMaximum number of results (default: 50)
sortNoSort order
groupByNoFields to group by (for aggregate). Example: ["resource_name", "status"]
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 reveals that traces auto-generate metrics in a specific namespace, which is a behavioral trait. However, it does not disclose whether the tool is read-only, rate limits, or authentication requirements. The description adds some context but is not comprehensive.

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 informative but somewhat lengthy; it front-loads the purpose and actions, then provides filter examples and APM metrics guidance. Most sentences add value, though the APM metrics section could be more concise. Overall, it is structured well with clear sections.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given 17 parameters and no output schema, the description covers actions, filter details, and includes a crucial note about auto-generated metrics and percentile querying. This provides a comprehensive understanding of the tool's capabilities and relationships with other tools.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, with every parameter having a description. The description adds value by providing examples and format details for parameters like 'from' and 'to' (ISO 8601, relative), 'httpStatus', and 'minDuration'. This goes beyond the basic schema, earning a score above the baseline of 3.

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 clearly states the tool's purpose: 'Analyze APM traces for request flow and latency debugging.' It lists specific actions (search, aggregate, services) and resources (traces). This differentiates it from sibling tools like logs, metrics, etc., which handle different data types.

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

Usage Guidelines4/5

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

The description provides context on when to use this tool: for APM trace analysis, with key filters for latency and status. It explicitly directs users to the metrics tool for percentile queries, offering an alternative. However, it does not explicitly state when not to use it or provide exclusions for specific scenarios.

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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