Now Available — Connect Datadog + AI

# AI-Power Your Datadog in 2 Clicks

MCPEngage connects Datadog to any AI model via MCP.
Query metrics, investigate incidents, and build dashboards — all through conversation.

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View on GitHub
app.mcpengage.com/datadog

#### High CPU on prod-api-12

Triggered 4 min ago • Critical

Firing
Production API cluster

#### Elevated error rate

Triggered 12 min ago • Warning

Warning
Staging Web service
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0+
Monitoring Tools
$0
Setup Cost
0min
Install Time
24/7
AI Observability
Quick Install

## Up and Running in
One Command

~/projects
Open source — view the full code on GitHub
The Difference

## Before vs. After

### Before MCPEngage

- Dashboard surfing

  Toggle between 15 different Datadog dashboards trying to correlate CPU, memory, and error rates

- Alert fatigue

  Slack alerts fire constantly — you check Datadog UI, find the host, check logs, dig through metrics

- Manual queries

  Want to know "which service is slowest?" — you write custom PromQL, wait 30 seconds, format results

- Incident chaos

  On-call gets paged — spend 10 minutes finding the right dashboard, host, and time window

### After MCPEngage

- One-question visibility

  "Show me prod CPU usage in the last hour" — instant graph with anomaly highlights

- Smart incident triage

  "What's wrong with prod-api-12?" — AI pulls CPU, memory, logs, and recent deploys in one view

- Natural metric queries

  "Which service has the highest error rate?" — AI queries, ranks, and explains in plain English

- Instant troubleshooting

  "Show me all errors from checkout service in the last 10 minutes" — logs + context delivered

The Problem

## Your Infrastructure Is
A Black Box

Datadog collects everything, but finding the right metric at 3am is still a nightmare.

### Metric Overload

You're tracking 10,000+ metrics across services, hosts, and containers. Finding the one that explains why checkout is slow requires dashboard archaeology.

### Alert Storm Chaos

Monitors fire all the time. Half are false positives. The other half require 5 clicks to understand context. By the time you investigate, the incident has evolved.

### Log Labyrinth

Error logs are in Datadog. Stack traces are in Sentry. Recent deploys are in GitHub. Correlating them requires opening six browser tabs and manual detective work.

The Solution

## Three Steps to
AI-Powered Monitoring

1

### Connect Your Datadog

Paste your Datadog API and application keys from account settings. MCPEngage discovers all metrics, monitors, dashboards, and logs — building 58+ tools automatically. No code required.

2

### Ask in Plain English

"Show me prod CPU spikes." "What's firing right now?" "Which service is slowest?" Your AI understands observability like a veteran SRE.

3

### Automate Incident Response

Set up workflows: triage alerts, correlate metrics, query logs, notify on-call, create dashboards, and post summaries to Slack — all running 24/7.

Features

## Everything to
Supercharge Observability

58+ Datadog tools accessible through one natural-language interface.

### Metric Intelligence

Query any metric with natural language. "Show me average response time by service last week."

### Monitor Management

Create, update, mute, and resolve monitors through conversation. "Mute the staging alerts."

### Dashboard Builder

Generate custom dashboards on demand. "Create a dashboard for checkout service performance."

### Log Explorer

Search logs, filter by tags, and correlate with metrics. "Show me all errors from prod-api in the last hour."

### Incident Correlation

AI connects alerts, metrics, logs, and deploys to surface root cause. "Why is checkout slow?"

### Anomaly Detection

Spot unusual patterns in metrics automatically. "Which metrics are behaving abnormally?"

FAQ

## Common Questions

MCP (Model Context Protocol) is an open standard created by Anthropic that lets AI models securely connect to external tools and data sources. Think of it as a USB port for AI — MCPEngage uses MCP to give your AI real-time access to Datadog.
You provide a Datadog API key and application key from your account settings. MCPEngage uses the Datadog API to create 58+ tools covering metrics, monitors, dashboards, and logs. Your credentials are encrypted and never stored on our servers.
Absolutely. MCPEngage runs locally or in your own infrastructure — monitoring data never passes through our servers. API keys are encrypted at rest. You control all access permissions.
MCPEngage is designed to complement the Datadog UI, not replace it. Use AI for quick queries, incident triage, and automation. Use the UI for deep investigation and visual exploration.
MCPEngage is free during the beta period. After launch, pricing starts at $29/month per platform connection. Enterprise plans with custom integrations and priority support are available on request.
Yes! MCPEngage supports 66+ platforms including PagerDuty, Slack, GitHub, AWS, and many more. Each platform gets its own MCP server with platform-specific tools. Connect as many as you need.

## Start Automating Monitoring
Today

Join thousands of engineering teams using MCPEngage to supercharge their Datadog workflows.

### You're on the list!

We'll notify you as soon as MCPEngage for Datadog is ready.

Free during beta. No credit card required.