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One MCP connection. Full Datadog context. No more tab-switching — just ask.
Stop navigating Datadog dashboards to piece together what's happening. Ask your AI agent for infrastructure health, service error rates, latency trends, log anomalies, and alert status across every environment — answered in plain language.
Your AI agent reads harmonized data across 500+ platforms. "Cost" in Google Ads and "spend" in Meta Ads resolve to the same field automatically.
Create monitors, update alert thresholds, silence maintenance windows, and manage dashboards — all through natural language. No more clicking through Datadog's UI to set up routine observability housekeeping.
250+ governance rules enforce naming conventions, budget limits, and KPI thresholds. SOC 2 Type II certified.
Set AI-powered watches on your system health that go beyond threshold alerts. Get context-aware summaries of what's degrading, which deploys correlate with regressions, and what needs immediate investigation — before customers feel the impact.
Automated weekly reports, anomaly flagging, and budget alerts — all from a single conversation. No more morning check-ins across 5 dashboards.
Create monitors, update alert thresholds, silence maintenance windows, and manage dashboards — all through natural language. No more clicking through Datadog's UI to set up routine observability housekeeping.
Every phase runs through the same MCP connection. One protocol, all platforms, full governance. No switching between tools.
During incidents, Datadog triggers dozens of cascading alerts across correlated services. The on-call engineer has to distinguish root cause from downstream symptoms in real time, while simultaneously managing stakeholder comms. Most of the alert noise is redundant — the same root cause triggering 30 child monitors — but there's no automated way to group and prioritize it.
Ask your AI agent to triage the alert storm. It reads all active Datadog monitors, groups correlated alerts by root cause hypothesis, identifies which services are primary versus downstream, and returns a prioritized incident brief in under a minute.
A latency spike appears on the Datadog graph. Was it the 3pm deploy? The infrastructure resize? The traffic surge from the email campaign? Answering this question requires opening Datadog, overlaying deploy markers, switching to APM traces, checking CI/CD logs, and building a timeline manually — a process that takes 45 minutes when the answer is needed in 5.
Improvado MCP correlates Datadog metrics with deployment and change events automatically. One prompt gives you a timeline: what changed, when, and how each metric responded — so you can identify the cause and roll back or fix with confidence.
Each team maintains its own Datadog dashboards — infrastructure, platform, product, security. Getting a unified health picture means opening five dashboards, interpreting five different layouts, and mentally aggregating the signals. There's no single view, so cross-team issues that span multiple services are invisible until someone manually connects the dots.
Ask your AI agent for a unified health summary that spans all your Datadog data. It aggregates metrics across teams, services, and environments into a single coherent briefing — formatted for your audience, whether that's an on-call runbook or a leadership update.
Same MCP connection, different workflows for every team member. Agency CEOs get portfolio health. Media Strategists get campaign QA. Analysts get cross-platform reports. Account Managers get auto-generated QBR decks. Creative Directors get performance-based briefs.
Each role asks in natural language. The MCP server handles the complexity — rate limits, auth, schema normalization, governance — behind the scenes.
Datadog MCP is a Model Context Protocol server that connects your Datadog observability data to AI agents like Claude, ChatGPT, and Gemini. It lets you query metrics, logs, traces, alerts, and infrastructure data in natural language — and take write actions like creating monitors or silencing alerts — without navigating the Datadog UI.
Metrics, logs, traces, APM service data, infrastructure host and container stats, monitors and alert status, SLOs, dashboards, events, and deployment markers. You can query raw data, aggregate trends, or ask for synthesized health summaries across any combination of services and environments.
Both. Read operations include querying metrics, logs, and alert states. Write operations include creating and modifying monitors, silencing alerts, creating dashboards, and updating notification policies. All write actions require an API key with the appropriate Datadog permissions.
Yes. Improvado supports multiple Datadog org credentials. You can query specific organizations or ask for aggregated health summaries across all connected orgs in a single prompt.
Yes. Improvado stores Datadog API and Application keys in an encrypted vault certified to SOC 2 Type II. The AI agent never accesses your credentials directly — all requests go through Improvado's secure proxy layer.
Under 60 seconds. Add your Datadog API key and Application key, configure the MCP server URL in your AI agent, and you're querying. Improvado users with Datadog already connected can start immediately.
Connect your data to an AI agent in under 60 seconds. The closed loop starts with one conversation.
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