Datadog MCP Server: Query Monitors, Dashboards, and Logs with AI

# Datadog MCP Server: Query Monitors, Dashboards, and Logs with AI

During an incident, you switch between your terminal, Datadog dashboards, log explorer, and Slack. Your AI coding assistant could help investigate if it could see your metrics and logs. MCP makes that possible.

With DataFaucet, you can create a Datadog MCP server that gives Claude, Cursor, and other AI tools direct access to your monitoring data.

What Your AI Can Do With Datadog Access

Once connected, your AI tools can:

• Check monitor status across all your services
• Query log data with search filters and time ranges
• Pull metric values from dashboards and graphs
• List active incidents and their severity
• Search APM traces for specific errors
• Get host/container metrics for capacity planning

How It Works

DataFaucet captures the API layer between the Datadog web UI and their backend. Log into Datadog in the cloud browser, interact with dashboards and log explorer, and DataFaucet captures every API call.

1. Enter app.datadoghq.com in DataFaucet
2. Browse dashboards, run log queries, check monitors
3. DataFaucet captures the underlying API traffic
4. Deploy as a hosted MCP server

Connect from any AI tool:

claude mcp add datadog https://datafaucet.dev/api/mcp/YOUR_SERVER_ID

Example Prompts After Connecting

• "Are any monitors currently alerting?"
• "Show me error logs from the payment service in the last hour"
• "What's the p99 latency for the /api/checkout endpoint today?"
• "How many 5xx errors hit production in the last 24 hours?"
• "List all hosts with CPU above 80% right now"
• "Pull the deploy frequency metric for the last 30 days"

Why This Matters for Incident Response

When you're debugging at 2am, context-switching between tools slows you down. With a Datadog MCP server, you can ask your AI assistant:

"Check if the error rate spike correlates with the deploy that went out at 11pm. Pull the error logs from the auth service and the deploy events from the last 3 hours."

Your AI does the Datadog querying while you focus on the fix.

Common Workflows

Incident investigation: "Error rate spiked 10 minutes ago. Pull the logs around that timestamp filtered to ERROR level and show me the top error messages."

Capacity planning: "Show me the memory usage trend for the worker fleet over the last 7 days. Are we approaching the threshold?"

Deploy validation: "Compare error rates before and after the last deploy. Any new error patterns?"

SLO monitoring: "What's our current burn rate on the checkout availability SLO? How many error budget minutes remain?"

Code context: "I'm looking at the payment handler code. What does Datadog show for this endpoint's latency percentiles and error rate?"

Security Considerations

• Datadog session tokens captured by DataFaucet have the same permissions as your user account
• Use a read-only Datadog role for the session you capture with
• The MCP server exposes only the operations you performed during capture
• API key for the MCP server is separate from Datadog credentials and rotatable

Works With Every MCP Client

Your Datadog MCP server works with Claude Desktop, Cursor, Windsurf, Codex, and any MCP-compatible client. Query metrics in Cursor while writing code, investigate incidents in Claude, automate reports from Codex.

Get Started

Create your Datadog MCP server in 60 seconds. Free tier includes 3 servers, no credit card required.

Related: Grafana MCP Server for dashboards, Sentry MCP Server for error tracking, PagerDuty MCP Server for incident management, AWS MCP Server for cloud infrastructure, Elasticsearch MCP Server for search clusters, Snowflake MCP Server for data warehouse queries, GitHub MCP Server for repos and PRs, PostgreSQL MCP Server for database queries.