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brukhabtu

Datadog MCP Server

by brukhabtu

SearchIncidents

Search and filter incident data on Datadog MCP Server using custom queries, sorting options, and pagination to manage and analyze specific incidents effectively.

Instructions

Search for incidents matching a certain query.

Query Parameters:

  • include: Specifies which types of related objects should be included in the response.

  • query (Required): Specifies which incidents should be returned. The query can contain any number of incident facets joined by ANDs, along with multiple values for each of those facets joined by ORs. For example: state:active AND severity:(SEV-2 OR SEV-1).

  • sort: Specifies the order of returned incidents.

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

  • page[offset]: Specific offset to use as the beginning of the returned page.

Responses:

  • 200 (Success): OK

    • Content-Type: application/json

    • Response Properties:

      • included: Included related resources that the user requested.

    • Example:

{
  "data": "unknown_type",
  "included": [
    "unknown_type"
  ],
  "meta": "unknown_type"
}
  • 400: Bad Request

    • Content-Type: application/json

    • Response Properties:

      • errors: A list of errors.

    • Example:

{
  "errors": [
    "Bad Request"
  ]
}
  • 401: Unauthorized

    • Content-Type: application/json

    • Response Properties:

      • errors: A list of errors.

    • Example:

{
  "errors": [
    "Bad Request"
  ]
}
  • 403: Forbidden

    • Content-Type: application/json

    • Response Properties:

      • errors: A list of errors.

    • Example:

{
  "errors": [
    "Bad Request"
  ]
}
  • 404: Not Found

    • 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
includeNoObject related to an incident.
page[offset]NoSpecific offset to use as the beginning of the returned page.
page[size]NoSize for a given page. The maximum allowed value is 100.
queryYesSpecifies which incidents should be returned. The query can contain any number of incident facets joined by `ANDs`, along with multiple values for each of those facets joined by `OR`s. For example: `state:active AND severity:(SEV-2 OR SEV-1)`.
sortNoThe ways searched incidents can be sorted.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataYes
metaNo
includedNoIncluded related resources that the user requested.
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 includes pagination details (e.g., 'page[size]' max of 100) and error responses (e.g., 429 for rate limits), which adds useful context beyond basic functionality. However, it lacks information on permissions, authentication requirements, or potential side effects, leaving gaps for a tool that likely involves data access.

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

Conciseness2/5

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

The description is overly verbose and poorly structured, including extensive HTTP response details (e.g., multiple error codes with examples) that are redundant with typical API conventions and output schemas. This clutter detracts from core information, making it less efficient for an AI agent to parse. The front-loaded purpose is clear, but the bulk of the text does not earn its place.

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, 1 required) and the presence of an output schema (implied by response details), the description is reasonably complete. It covers key aspects like query syntax, pagination, and error handling, which are crucial for usage. However, the inclusion of verbose HTTP response examples adds noise without substantial value, slightly reducing completeness.

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 description provides detailed parameter explanations, but the input schema has 100% description coverage, meaning the schema already documents all parameters thoroughly. The description repeats some schema details (e.g., for 'query' and 'page[size]'), adding minimal extra value. Since schema coverage is high, the baseline score of 3 is appropriate, as the description doesn't significantly enhance parameter 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: 'Search for incidents matching a certain query.' It specifies the verb ('search') and resource ('incidents'), making the function unambiguous. However, it does not explicitly differentiate from sibling tools like 'ListIncidents' or 'GetIncident', which might offer different scopes or functionalities, so it doesn't reach 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?

The description provides no guidance on when to use this tool versus alternatives. It mentions query parameters but does not explain scenarios where this search tool is preferred over other incident-related tools (e.g., 'ListIncidents' for unfiltered lists or 'GetIncident' for single incidents). This lack of contextual usage advice limits its effectiveness 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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