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
Installation
From Source
git clone https://github.com/brukhabtu/datadog-mcp.git
cd datadog-mcp
pip install -e .
Using Docker
docker pull ghcr.io/brukhabtu/datadog-mcp:latest
Configuration
Required Environment Variables
DATADOG_API_KEY="your-datadog-api-key"
DATADOG_APP_KEY="your-datadog-application-key"
Optional Environment Variables
DATADOG_BASE_URL="https://api.datadoghq.com" # Default US site
DATADOG_TIMEOUT=30 # Request timeout in seconds
MCP_TRANSPORT=stdio # Transport method (stdio/websocket)
MCP_PORT=8000 # Port for WebSocket transport
MCP_LOG_LEVEL=INFO # Logging level
MCP_ENABLE_SECURITY_FILTERING=true # Enable read-only filtering
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
# Run with default stdio transport
datadog-mcp
# Run with WebSocket transport
datadog-mcp --transport websocket --port 8000
# Run with debug logging
datadog-mcp --log-level DEBUG
Docker
# Run with environment file
docker run --env-file .env ghcr.io/brukhabtu/datadog-mcp:latest
# Run with individual environment variables
docker run -e DATADOG_API_KEY=your-key \
-e DATADOG_APP_KEY=your-app-key \
ghcr.io/brukhabtu/datadog-mcp:latest
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
{
"mcpServers": {
"datadog": {
"command": "docker",
"args": [
"run", "--rm", "-i",
"--env", "DATADOG_API_KEY",
"--env", "DATADOG_APP_KEY",
"ghcr.io/brukhabtu/datadog-mcp:latest"
],
"env": {
"DATADOG_API_KEY": "your-datadog-api-key",
"DATADOG_APP_KEY": "your-datadog-application-key"
}
}
}
}
Or use the native installation:
{
"mcpServers": {
"datadog": {
"command": "datadog-mcp",
"args": ["--transport", "stdio"],
"env": {
"DATADOG_API_KEY": "your-datadog-api-key",
"DATADOG_APP_KEY": "your-datadog-application-key"
}
}
}
}
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:
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):
MCP_ENABLE_SECURITY_FILTERING=false
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
# Clone the repository
git clone https://github.com/brukhabtu/datadog-mcp.git
cd datadog-mcp
# Create virtual environment
python -m venv venv
source venv/bin/activate # On Windows: venv\Scripts\activate
# Install in development mode
pip install -e .
Running Tests
Building Docker Image
docker build -t datadog-mcp:local .
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
- 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.