Skip to main content
Glama
ClaudioLazaro

MCP Datadog Server

aggregate_logs_analytics

Aggregate log events into buckets to compute metrics and timeseries for monitoring and analysis in Datadog.

Instructions

The API endpoint to aggregate events into buckets and compute metrics and timeseries.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

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 mentions aggregation and computation but does not disclose behavioral traits such as whether this is a read-only operation, requires specific permissions, has rate limits, or affects data. This leaves significant gaps for an agent to understand how to invoke it safely and effectively.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence that directly states the tool's purpose without unnecessary words. It is appropriately sized for a tool with no parameters, though it could be slightly more specific to improve clarity.

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?

Given the complexity of an analytics tool with no annotations, no output schema, and many sibling tools, the description is incomplete. It lacks details on what events are aggregated (e.g., log events), the format of results, or how it differs from other aggregation tools, making it inadequate for an agent to use effectively without additional context.

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% coverage, meaning no parameters are documented in the schema. The description does not add parameter details, but since there are no parameters, this is acceptable. The baseline for 0 parameters is 4, as the description need not compensate for missing param info.

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

Purpose3/5

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

The description states the tool aggregates events into buckets and computes metrics and timeseries, which clarifies the verb (aggregate/compute) and resource (events). However, it does not distinguish this tool from sibling aggregation tools like aggregate_ci_pipelines_analytics or aggregate_rum_analytics, leaving the specific scope (logs) implied but not explicit.

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. It does not mention prerequisites, context, or exclusions, and with many sibling aggregation tools present, the agent lacks direction on selecting this specific logs analytics tool over others.

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/ClaudioLazaro/mcp-datadog-server'

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