MCP Datadog Server
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- AlicenseAqualityCmaintenanceEnables AI assistants to search logs, query metrics, manage dashboards, analyze APM traces, and control monitors via Datadog APIs.30MIT
- AlicenseNot gradedqualityDmaintenanceEnables AI assistants to interact with Datadog's observability platform via natural language, covering metrics, logs, APM, monitors, dashboards, incidents, and infrastructure.6631MIT
- AlicenseNot gradedqualityDmaintenanceEnables AI assistants to query Datadog metrics, logs, monitors, security signals, and billing data through natural language.MIT
- AlicenseNot gradedqualityDmaintenanceEnables AI assistants to interact with DataDog's observability platform through a standardized interface. Supports monitoring infrastructure, managing events, analyzing logs and metrics, and automating operations like alerts and downtimes.1MIT
- AlicenseCqualityAmaintenanceEnables interaction with Datadog APIs through automatically generated tools from Postman collections. Supports monitoring operations, log management, metrics submission, and other Datadog functionality through natural language.1009Apache 2.0
- AlicenseNot gradedqualityCmaintenanceEnables interaction with Datadog APIs through natural language, supporting full CRUD operations on metrics, monitors, dashboards, logs, infrastructure, and more.4MIT
TDQS
Scored across 16 tools
Most tools are distinct, but the three service dependency tools (get_apm_service_dependencies, get_service_dependencies, get_service_dependencies_multi_env) have highly overlapping purposes and could be easily misselected by an agent. Other tools like list_metrics vs query_metrics are clearly separated, but the dependency trio introduces ambiguity.
Tool names consistently use snake_case with a verb_noun pattern (get_, list_, search_, query_, aggregate_). The verbs are predictable and align with their actions. Minor deviation: get_ prefixes are used for both single items (get_metric_metadata) and collections (get_service_dependencies), but this is not overly confusing.
16 tools is on the higher end of the recommended range, but it covers multiple Datadog features (metrics, logs, events, monitors, APM, dependencies) reasonably. Each tool serves a distinct function within these domains, so the count is justified, though it feels slightly heavy for a single server.
The set provides broad read-only coverage for Datadog's main observability areas, but it lacks any write operations (create, update, delete monitors, events, etc.). There are also gaps like dashboards and trace detail. The service dependency trio is overrepresented while monitor management is incomplete, leaving agents unable to perform lifecycle actions.