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Discover Datadog MCP tools by natural language query. Returns matching tool names and descriptions to help you navigate and call the appropriate tool.

Instructions

Discover available tools by natural language query. Returns matching tool names + descriptions across all 158+ tools. Use this first to navigate the surface efficiently — call this, then call the specific tool you need.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesNatural language query. Discover tools across the 158-tool Datadog MCP surface — call this first to find the right tool.
categoryNoRestrict search to a specific category
limitNoMax results (default 20)
Behavior4/5

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

Annotations already indicate readOnlyHint=true and openWorldHint=true. The description adds that it returns tool names and descriptions covering all 158+ tools, which is useful behavioral context.

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?

Two concise sentences: first states purpose and output, second gives usage guidance. No wasted words, front-loaded with action.

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

Completeness5/5

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

Without an output schema, the description adequately explains return value (matching tool names + descriptions). Given low complexity and annotations covering safety, this is complete for agent decision-making.

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?

Schema coverage is 100%, so all parameters already have descriptions. The description does not add extra parameter-level details beyond what is in the schema.

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

Purpose5/5

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

The description clearly states it discovers available tools via natural language query and returns tool names and descriptions. It distinguishes itself from sibling tools by being the tool to find the right tool before calling specific ones.

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

Usage Guidelines5/5

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

Explicitly advises 'Use this first to navigate the surface efficiently — call this, then call the specific tool you need.' This provides clear when-to-use guidance and implies not to use when already knowing the target tool.

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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