"datadog" matching MCP servers:

provide access to monitor and cluster logs from datadog

Enables AI assistants to search logs, query metrics, manage dashboards, analyze APM traces, and control monitors via Datadog APIs.

An MCP server that provides comprehensive read/write access to Datadog APIs, enabling management of monitors, dashboards, logs, incidents, and more via natural language commands.

Enables comprehensive Datadog monitoring capabilities including CI/CD pipeline management, service logs analysis, metrics querying, monitor and SLO management, service definitions retrieval, and team management through Claude and other MCP clients.

Enables AI assistants to query Datadog metrics, logs, monitors, security signals, and billing data through natural language.

Enables interaction with Datadog APIs through natural language, supporting full CRUD operations on metrics, monitors, dashboards, logs, infrastructure, and more.

A read-only MCP server that exposes tools to query Datadog monitors and logs, and AWS CloudWatch Logs, and to group recurring errors by fingerprint. Designed for use with Claude Code to diagnose issues and propose fixes.

A FastMCP server that provides DataDog log search and monitoring with service-aware filtering, preview-execute workflow, and response size safeguards.

A Model Context Protocol (MCP) server that provides comprehensive Datadog monitoring capabilities, enabling Claude to manage CI/CD pipelines, analyze logs, query metrics, and handle monitors and SLOs.

A Model Context Protocol server that enables AI assistants to interact with Datadog's observability platform through natural language.

Lets you inspect a Datadog organization's usage and answer cost questions in plain English, helping identify savings opportunities.

A lightweight Model Context Protocol server that enables creating, managing, and querying model contexts with integrated Datadog metrics and monitoring.

Connects AI assistants to OpenTelemetry trace backends such as Jaeger, Tempo, Traceloop, and Datadog, enabling natural-language searching of traces and spans, error discovery, and service listing. It also provides LLM-specific analytics, including token usage aggregation, model performance comparison, and identification of the most expensive or slowest traces.

Enables automated analysis of test suite traces to identify timing races and state pollution, helping detect flaky test non-determinism in CI/CD workflows such as Datadog CI or Trunk.

A modular MCP server exposing tools for integrating with services like GitHub, Redash, Jenkins, Figma, Jira, Confluence, Teams, Datadog, PagerDuty, Slack, and Presto, enabling users to manage these platforms through natural language via an MCP client.

Consolidates Salesforce, CMA Gateway, Optix SQL clusters, Confluence/G3 knowledge base, Datadog observability, and UPS/FDS platform into a single SSE/JSON-RPC daemon exposing 168 canonical tools and 15 resources. Enables AI agents and IDEs to search and manage cases, chains, databases, documentation, telemetry, and platform configurations through natural language.