Datadog MCP Server

list_metrics

Retrieve active metric names from Datadog monitoring platform using timeframe and tag filters to identify relevant performance data.

Instructions

List active metric names from Datadog

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "list_metrics"
  }
}

Input Schema

Name	Required	Description	Default
`from`	No	Start of the timeframe (in seconds since Unix epoch) to list active metrics. Defaults to 24h ago if omitted.
`tagFilter`	No	Filter metrics that have been submitted with the given tags.

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.6.14Jan 26, 2026

TDQS

C2.9/5.0

Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the action ('List active metric names') but doesn't describe what 'active' means, whether this is a read-only operation, potential rate limits, authentication needs, or the format of returned data. This leaves significant gaps for a tool with no annotation coverage.

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, efficient sentence that directly states the tool's purpose without any wasted words. It's appropriately sized and front-loaded, making it easy for an agent to parse quickly.

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?

Given the lack of annotations and output schema, the description is incomplete. It doesn't explain what 'active' metrics are, how results are returned (e.g., pagination, format), or behavioral constraints. For a tool with no structured safety or output information, more context is needed to adequately guide an agent.

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?

The input schema has 100% description coverage, with clear documentation for both optional parameters ('from' and 'tagFilter'). The description adds no additional parameter information beyond what the schema provides, so the baseline score of 3 is appropriate as the schema does the heavy lifting.

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 clearly states the verb ('List') and resource ('active metric names from Datadog'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'query_metrics' or 'get_monitors', which prevents a perfect score.

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?

No guidance is provided on when to use this tool versus alternatives like 'query_metrics' or 'get_monitors'. The description lacks any context about use cases, prerequisites, or exclusions, leaving the agent to infer usage from the tool name alone.

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

Deploy Server