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MCP Datadog Server

MCP Datadog Server

by ClaudioLazaro
OverviewSchemaSourceRelated ServersDiscussionsAdmin
JavaScript
Remote

search_slos

Retrieve service level objective objects from your Datadog organization to monitor and analyze performance metrics and compliance with service agreements.

Instructions

Get a list of service level objective objects for 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": "search_slos"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

B3.2/5.0
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. It states this is a 'Get' operation (implying read-only), but doesn't disclose any behavioral traits like authentication requirements, rate limits, pagination, sorting options, or what happens when no SLOs exist. For a list operation with zero annotation coverage, this leaves significant gaps.

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 communicates the core purpose without unnecessary words. It's front-loaded with the key action ('Get a list') and doesn't waste space on redundant information. Every word earns its place.

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?

For a simple list operation with no parameters and no output schema, the description is minimally adequate. However, without annotations or output schema, it should ideally mention what the return format looks like (e.g., list of objects, JSON structure) or any implicit filtering. The description covers the basic 'what' but leaves the 'how' and 'what you get' unspecified.

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 the schema fully documents the absence of parameters. The description doesn't need to add parameter information, and it correctly implies this tool requires no inputs by not mentioning any. This meets expectations for a parameterless tool.

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 ('Get') and resource ('service level objective objects'), making the purpose understandable. It specifies the scope ('for your organization'), which adds useful context. However, it doesn't distinguish this from sibling tools like 'get_slos' or 'slos_list', which appear to serve similar purposes.

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 sibling tools like 'get_slos' and 'slos_list' available, there's no indication of differences in functionality, filtering capabilities, or appropriate use cases. The agent must infer usage from tool names alone.

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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