Skip to main content
Glama
us-all

datadog-mcp-server

by us-all

search-tools

Find the right Datadog MCP tool by describing what you need in natural language. Returns matching tool names and descriptions to guide your next action.

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)
Behavior5/5

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 discloses that the tool performs a read-only search and returns tool names and descriptions. There are no side effects or restrictions mentioned, which is appropriate for a discovery tool.

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 concise: three sentences that front-load the purpose, output, and usage guidance. Every sentence adds value with no redundancy.

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?

For a simple search tool without an output schema, the description sufficiently explains what the tool does and what it returns (tool names + descriptions). It also provides strategic context for calling it first, making the tool complete for its intended use.

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?

The input schema has 100% description coverage, so the schema already fully documents the parameters. The description does not add new parameter-level semantics beyond the schema. Baseline of 3 is appropriate.

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 the tool's purpose: 'Discover available tools by natural language query' and specifies the output: 'Returns matching tool names + descriptions across all 158+ tools'. It distinguishes itself from the many sibling tools by being a meta-tool for discovery.

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?

The description provides explicit guidance: 'Use this first to navigate the surface efficiently — call this, then call the specific tool you need.' This clearly tells the agent when and how to use this tool relative to the other tools.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/us-all/datadog-mcp-server'

If you have feedback or need assistance with the MCP directory API, please join our Discord server