Datadog MCP Server

get-synthetic-tests

List Datadog synthetic tests, including API and browser tests, and retrieve names, types, status, locations, and tags to identify failing tests.

Instructions

List Datadog Synthetic tests (API and browser). Use for 'show all synthetic tests', 'what API tests exist', or 'which tests are failing'. Returns test names, types, status, locations, and tags.

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": "get-synthetic-tests"
  }
}

Input Schema

Name	Required	Description
`pageSize`	No	Number of tests per page
`pageNumber`	No	Page number for pagination
`type`	No	Filter by test type ('api' or 'browser')
`locations`	No	Comma-separated location filter

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.11.0May 26, 2026

TDQS

A4/5.0

Behavior3/5

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

With no annotations, the description partially covers behavior by listing returned fields (names, types, status, locations, tags), but lacks detail on pagination, ordering, or read-only nature. It neither contradicts nor fully discloses behavioral traits.

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 two sentences long, front-loads the core purpose, and includes example queries without unnecessary words, making it highly concise and structured.

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 no output schema, the description explains returned fields (names, types, status, locations, tags). It implicitly covers filtering by type and locations but omits pagination behavior and error cases, which are minor gaps for a listing tool.

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 coverage is 100% with descriptions for all 4 parameters. The description adds no new parameter-level semantics beyond what the schema provides, so baseline 3 is appropriate; the mention of returned fields improves overall understanding but does not directly enhance parameter semantics.

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 'List Datadog Synthetic tests' with specific verb and resource, and includes examples like 'show all synthetic tests' and 'which tests are failing', distinguishing it from sibling tools that focus on different resources.

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 explicit usage examples ('show all synthetic tests', 'what API tests exist', 'which tests are failing') but does not mention when to avoid using this tool or suggest alternatives, which is acceptable given its distinct purpose.

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

Deploy Server