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MCP Datadog Server

MCP Datadog Server

by ClaudioLazaro
OverviewSchemaSourceRelated ServersDiscussionsAdmin
JavaScript
Remote

create_ci_pipelines

Send pipeline execution events to Datadog for CI/CD monitoring and tracking, supporting timestamps up to 18 hours in the past.

Instructions

Send your pipeline event to your Datadog platform over HTTP. For details about how pipeline executions are modeled and what execution types we support, see Pipeline Data Model And Execution Types.

Pipeline events can be submitted with a timestamp that is up to 18 hours in the past.

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": "create_ci_pipelines"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A3.6/5.0
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 discloses that events are sent over HTTP and have a timestamp constraint, but lacks details on authentication, rate limits, error handling, or what happens after submission (e.g., confirmation). It adds some behavioral context but is incomplete for a mutation tool.

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 front-loaded with the core purpose in the first sentence, followed by a documentation link and a constraint. Both sentences are necessary and efficient, with no wasted words.

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

Completeness3/5

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

Given no annotations, no output schema, and 0 parameters, the description is moderately complete. It covers the purpose and a constraint but lacks details on authentication, response format, or error cases, which are important for a tool that sends data over HTTP.

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?

With 0 parameters and 100% schema description coverage, the baseline is high. The description doesn't need to explain parameters, but it implies that pipeline event data is sent, though it doesn't specify the data format or required fields. It adds minimal value 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 action ('send your pipeline event') and target ('to your Datadog platform over HTTP'), specifying it's for CI pipelines. It distinguishes from siblings by focusing on event submission rather than analytics or other operations, though it doesn't explicitly name alternatives.

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

Usage Guidelines3/5

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

The description implies usage for submitting pipeline events to Datadog and mentions a timestamp constraint (up to 18 hours in the past), but provides no explicit guidance on when to use this tool versus alternatives like aggregate_ci_pipelines_analytics or other create_* tools. The link to documentation offers context but isn't direct guidance.

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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