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Glama
tuno-dev

Datadog MCP Server

by tuno-dev

Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault
DD_API_KEYYesYour Datadog API key from the Datadog API Keys page
DD_APP_KEYYesYour Datadog application key from the Datadog API Keys page

Instructions

Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.

This server publishes no instructions, or was last inspected before Glama recorded them.

Capabilities

Server capabilities have not been inspected yet.

Tools

Functions exposed to the LLM to take actions

NameDescription
search_logsC

Tool for searching Datadog logs

search_spansC

Tool for searching Datadog trace spans

aggregate_spansC

Tool for aggregating Datadog trace spans

Prompts

Interactive templates invoked by user choice

NameDescription

No prompts

Resources

Contextual data attached and managed by the client

NameDescription

No resources

TDQS

C2.9/5.0

Scored across 3 tools

Disambiguation4/5

The three tools are mostly distinct, with 'aggregate_spans' focusing on aggregation of trace data, 'search_logs' targeting log data, and 'search_spans' targeting trace data. However, 'aggregate_spans' and 'search_spans' both operate on spans and could be confused for overlapping purposes, though their descriptions clarify one aggregates and the other searches.

Naming Consistency5/5

All tool names follow a consistent verb_noun pattern with snake_case, using 'aggregate' and 'search' as verbs paired with specific nouns like 'spans' and 'logs'. There are no deviations in naming style or convention.

Tool Count3/5

With only 3 tools, the server feels thin for a Datadog integration, which typically involves monitoring, metrics, dashboards, and alerts. While the tools cover traces and logs, the scope is limited, making it borderline appropriate for the apparent domain.

Completeness2/5

The tool surface has significant gaps for a Datadog server, missing core operations like querying metrics, managing dashboards, setting alerts, or accessing APM data beyond spans. Agents will struggle with incomplete coverage for common monitoring workflows.

Maintenance

ActivityInactive
ResponsivenessNo issues