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dreamiurg

Datadog MCP Server

by dreamiurg

get-containers

List all containers monitored by Datadog, including names, images, tags, state, and start time. Filter by tags, group by attribute, and paginate results.

Instructions

List containers monitored by Datadog. Use for 'show running containers', 'containers for web service', 'container status by image'. Returns container names, images, tags, state, and start time.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
filterTagsNoComma-separated tags (e.g., 'env:prod,service:web')
groupByNoGroup by attribute (e.g., 'short_image')
sortNoSort field (e.g., 'name', '-name')
pageSizeNoResults per page
pageCursorNoPagination cursor
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 states the tool returns container details (names, images, tags, state, start time), implying it is a read-only operation. However, it does not disclose authentication needs, rate limits, or side effects, which is a gap for a read tool with no annotations.

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 two sentences, front-loaded with the purpose, and provides immediate value with example queries. Every sentence is necessary and well-structured.

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?

The tool has 5 optional parameters and no output schema. The description covers the returned fields but does not explain how parameters like pagination (pageSize, pageCursor) or grouping (groupBy) affect results. For a simple list tool, it is adequate but not thorough.

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?

All 5 parameters have descriptions in the input schema (100% coverage), so the baseline is 3. The description does not add additional semantic context about the parameters beyond what is in the schema. No improvement or detriment.

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 lists containers monitored by Datadog and provides example use cases. However, it does not differentiate from the sibling 'list_containers' tool, leaving potential ambiguity.

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

Usage Guidelines4/5

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

The description explicitly mentions when to use the tool with natural language examples like 'show running containers'. It lacks information on when not to use it or alternatives, but given the examples, it provides adequate 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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