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MCP Datadog Server

MCP Datadog Server

by ClaudioLazaro
OverviewSchemaSourceRelated ServersDiscussionsAdmin
JavaScript
Remote

create_logs_config_pipelines

Configure log processing pipelines in Datadog to parse, enrich, and route log data for monitoring and analysis.

Instructions

Create a pipeline in your organization.

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_logs_config_pipelines"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

C2.9/5.0
Behavior2/5

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 states 'Create' which implies a mutation, but doesn't disclose behavioral traits like required permissions, whether it's idempotent, rate limits, or what happens on failure. This is a significant gap for a creation tool with zero 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 with no wasted words. It's appropriately sized and front-loaded, making it easy 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 complexity of a creation tool with no annotations, no output schema, and many sibling tools, the description is inadequate. It doesn't explain what a 'pipeline' entails, the expected outcome, or how it fits into the broader system, leaving the agent with insufficient context.

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?

The input schema has 0 parameters with 100% description coverage, so no parameters need documentation. The description doesn't add parameter details, but with no parameters, a baseline of 4 is appropriate as there's nothing to compensate for.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description 'Create a pipeline in your organization' clearly states the action (create) and resource (pipeline), but it's vague about what type of pipeline (logs configuration pipeline) and doesn't distinguish from sibling tools like 'create_ci_pipelines' or 'create_logs_config_archives'. It restates the tool name without adding specificity.

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. The description doesn't mention prerequisites, context, or exclusions, and with many sibling 'create_' tools present, this lack of differentiation leaves the agent without usage direction.

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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