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brukhabtu

Datadog MCP Server

by brukhabtu

ListRoles

Retrieve and manage all roles with their names and unique identifiers on the Datadog MCP Server. Filter, sort, and paginate results to streamline role identification and administration.

Instructions

Returns all roles, including their names and their unique identifiers.

Query Parameters:

  • page[size]: Size for a given page. The maximum allowed value is 100.

  • page[number]: Specific page number to return.

  • sort: Sort roles depending on the given field. Sort order is ascending by default. Sort order is descending if the field is prefixed by a negative sign, for example: sort=-name.

  • filter: Filter all roles by the given string.

  • filter[id]: Filter all roles by the given list of role IDs.

Responses:

  • 200 (Success): OK

    • Content-Type: application/json

    • Response Properties:

      • data: Array of returned roles.

    • Example:

{
  "data": [
    "unknown_type"
  ],
  "meta": "unknown_type"
}
  • 403: Authentication error

    • Content-Type: application/json

    • Response Properties:

      • errors: A list of errors.

    • Example:

{
  "errors": [
    "Bad Request"
  ]
}
  • 429: Too many requests

    • Content-Type: application/json

    • Response Properties:

      • errors: A list of errors.

    • Example:

{
  "errors": [
    "Bad Request"
  ]
}

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
filterNoFilter all roles by the given string.
filter[id]NoFilter all roles by the given list of role IDs.
page[number]NoSpecific page number to return.
page[size]NoSize for a given page. The maximum allowed value is 100.
sortNoSorting options for roles.name

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataNoArray of returned roles.
metaNo
Behavior3/5

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 adds value by detailing pagination (via page[size] and page[number]), sorting options, and filtering capabilities, which are useful beyond the input schema. However, it doesn't cover rate limits (implied by the 429 response but not explicitly stated), authentication needs (implied by the 403 response but not explained), or whether the operation is read-only (though 'Returns' suggests it).

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with the core purpose but becomes verbose by repeating parameter details already in the schema and including extensive HTTP response examples. While structured with sections, it includes redundant information (e.g., response properties and examples) that could be omitted if an output schema exists, reducing efficiency.

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 the tool's complexity (5 parameters, pagination, filtering) and the presence of an output schema (implied by 'Has output schema: true'), the description is fairly complete. It covers the purpose, parameters, and error responses, though it could benefit from more behavioral context (e.g., rate limits, auth details). The output schema likely handles return values, so the description doesn't need to explain them in depth.

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 schema description coverage is 100%, so the input schema already documents all parameters thoroughly. The description repeats parameter details (e.g., for filter, page[size], sort) without adding significant new meaning, such as examples for filter usage or clarification on filter[id] format. This meets the baseline for high schema coverage but doesn't enhance understanding beyond the schema.

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 tool's purpose: 'Returns all roles, including their names and their unique identifiers.' This specifies the verb ('Returns'), resource ('roles'), and scope ('all'), making it easy to understand. However, it doesn't explicitly differentiate from sibling tools like 'GetRole' (which likely fetches a single role), leaving room for slight ambiguity.

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 provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools like 'GetRole' (for single roles) or 'ListRoleUsers' (for users in roles), nor does it specify prerequisites, contexts, or exclusions for usage. This lack of comparative or contextual advice limits its utility for an AI agent.

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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