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MCP Datadog Server

MCP Datadog Server

by ClaudioLazaro
OverviewSchemaSourceRelated ServersDiscussionsAdmin
JavaScript
Remote

get_integration_aws_logs

List all configured Datadog-AWS Logs integrations to monitor and manage cloud infrastructure logs from AWS services within your Datadog account.

Instructions

List all Datadog-AWS Logs integrations configured in your Datadog account.

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_integration_aws_logs"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

B3.1/5.0
Behavior2/5

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

No annotations are provided, so the description carries full burden. While 'List all' implies a read-only operation, it doesn't disclose important behavioral aspects like whether this returns all integrations at once (vs paginated), what format the output takes, authentication requirements, or rate limits. For a tool with zero annotation coverage, this is insufficient.

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 that states exactly what the tool does with no wasted words. It's appropriately sized for a simple listing tool and gets straight to the point without unnecessary elaboration.

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?

For a tool with no annotations and no output schema, the description is inadequate. It doesn't explain what the output looks like (array of objects? what fields?), whether results are paginated, or any error conditions. Given the complexity of integration configurations and the lack of structured output documentation, more context is needed.

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 tool has 0 parameters with 100% schema description coverage, so the schema already fully documents the lack of inputs. The description doesn't need to add parameter information, and it correctly doesn't mention any parameters. A baseline of 4 is appropriate for zero-parameter tools.

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 verb ('List') and resource ('all Datadog-AWS Logs integrations'), making the purpose specific and understandable. However, it doesn't distinguish this tool from other 'get_integration_*' siblings like 'get_integration_aws' or 'get_integration_aws_logs_services', which could cause confusion about scope.

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. With many sibling tools like 'get_integration_aws' and 'get_integration_aws_logs_services', there's no indication of when this specific listing tool is appropriate versus other integration-related queries.

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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