Datadog MCP Server

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

Features

• Metrics: Query time-series data, list metrics, get metadata

• Logs: Search and filter log events

• APM: Access trace data, service maps, dependencies

• Infrastructure: Host information, container data, process metrics

• Dashboards: List and read dashboard configurations

• Monitors: Alert rules and status information

• Incidents: Incident tracking and management

• Service Catalog: Service definitions and relationships

• SLOs: Service level objectives and compliance data

• Usage: Account usage statistics

Related MCP server: FastMCP

Installation

From Source

Using Docker

Configuration

Required Environment Variables

Optional Environment Variables

Regional Endpoints

For different Datadog regions:

• US: https://api.datadoghq.com (default)

• EU: https://api.datadoghq.eu

• US3: https://api.us3.datadoghq.com

• US5: https://api.us5.datadoghq.com

• AP1: https://api.ap1.datadoghq.com

Usage

Command Line

Docker

Claude Desktop Integration

Add to your Claude Desktop configuration file:

macOS: ~/Library/Application Support/Claude/claude_desktop_config.json

Windows: %APPDATA%\Claude\claude_desktop_config.json

Linux: ~/.config/claude/claude_desktop_config.json

Or use the native installation:

OpenAPI Specification

The server requires the Datadog v2 API OpenAPI specification to be placed at: src/datadog_mcp/specs/datadog-v2.yaml

You can obtain this specification from:

• Datadog's API documentation

• Datadog's GitHub repositories

• Community-maintained specifications

Security

By default, the server runs with security filtering enabled (MCP_ENABLE_SECURITY_FILTERING=true), which restricts operations to read-only access. This includes:

Allowed Operations

• GET requests to query metrics, logs, traces, etc.

• Reading dashboards, monitors, and configurations

• Searching and filtering data

• Viewing usage statistics

Blocked Operations

• All POST, PUT, PATCH, DELETE operations

• User and API key management

• Organization settings modifications

• Any destructive actions

To disable security filtering (not recommended for production):

Example Interactions

Once configured, you can interact with Datadog through natural language:

• "Show me the error rate for my web service over the last hour"

• "List all active monitors that are alerting"

• "Get the CPU usage metrics for production hosts"

• "Show me recent incidents in the platform team"

• "What's our log volume usage this month?"

• "Find traces with high latency in the payment service"

• "Show me the service dependencies for the API gateway"

Development

Setup Development Environment

Running Tests

Building Docker Image

Architecture

The server follows the same architectural patterns as the Jira MCP implementation:

• FastMCP 2.0: Leverages automatic tool generation from OpenAPI specifications

• Security-First: Default read-only access with configurable filtering

• Environment Configuration: All settings via environment variables

• Docker-First: Containerized deployment for consistency

• Transport Flexibility: Supports both stdio and WebSocket transports

Troubleshooting

Authentication Errors

• Ensure both DATADOG_API_KEY and DATADOG_APP_KEY are set correctly

• Verify your keys have the necessary permissions in Datadog

• Check you're using the correct regional endpoint

Connection Issues

• Verify your network can reach the Datadog API

• Check if you need to configure proxy settings

• Ensure the timeout is sufficient for your queries

Missing Tools

• Verify the OpenAPI specification is present in src/datadog_mcp/specs/

• Check the server logs for any specification loading errors

• Ensure the specification version matches your Datadog API version

Contributing

Contributions are welcome! Please feel free to submit issues and pull requests.

License

MIT License - see LICENSE file for details

Credits

Based on the Jira MCP implementation pattern.