Datadog MCP Server
by TANTIOPE
MCP server exposing Datadog observability APIs for AI agents with logs, metrics, traces, monitors, dashboards, and more.
Install Datadog MCP Server
Pick your client, then add it in one click or paste the config.
~/Library/Application Support/Claude/claude_desktop_config.json{
"mcpServers": {
"tantiope-datadog-mcp-server": {
"command": "npx",
"args": [
"-y",
"datadog-mcp"
],
"env": {
"DD_API_KEY": "YOUR_VALUE_HERE",
"DD_APP_KEY": "YOUR_VALUE_HERE",
"DD_SITE": "YOUR_VALUE_HERE",
"MCP_DEFAULT_LIMIT": "YOUR_VALUE_HERE",
"MCP_DEFAULT_LOG_LINES": "YOUR_VALUE_HERE",
"MCP_DEFAULT_METRIC_POINTS": "YOUR_VALUE_HERE",
"MCP_DEFAULT_TIME_RANGE": "YOUR_VALUE_HERE",
"MCP_TRANSPORT": "YOUR_VALUE_HERE"
}
}
}
}
Settings → Developer → Edit Config, merge this into mcpServers, then fully quit and reopen Claude Desktop.
Values are written into the snippet above so you can paste it as is. They never leave your browser.
We couldn’t confirm it starts correctly
We ran the install command but it didn't respond within our test window — this can mean a slow first-time install rather than a real problem.
npx -y datadog-mcpNo response to initialize.
This is an experimental automated check and can have false negatives — missing environment variables, a slow cold install, etc. It doesn’t necessarily mean something’s wrong. Last checked 1mo ago.
Overview
Use cases
- Search and filter Datadog logs with complex queries
- Query and analyze APM traces by status, duration, and errors
- List and manage monitors, dashboards, and alerts
- Retrieve and correlate metrics, events, and incidents
- Inspect log processing pipelines, indexes, and archives
Key features
- Grep-like log search with filters
- APM trace filtering with duration/status/error queries
- Smart sampling modes for token efficiency
- Cross-correlation of logs, traces, and metrics
- Supports stdio and HTTP transport modes
- Extensive coverage of Datadog observability tools
Tools22
What Datadog MCP Server lets your agent do. Expand a tool for its parameters.
Security & health
What it can reach and how reliably it runs — from our own checks, not the maintainer’s claims.
Recent health check succeeded.
Supply-chain signal
No high-severity advisories surfaced by our automated scan.
Scanned 10d ago via OSV.dev · datadog-mcp (npm)
Adoption & maintenance
Factual signals from GitHub, npm, and our automated checks — not a rating.
From the project README
Datadog MCP Server
DISCLAIMER: This is a community-maintained project and is not officially affiliated with, endorsed by, or supported by Datadog, Inc. This MCP server utilizes the Datadog API but is developed independently.
MCP server providing AI assistants with full Datadog observability access. Features grep-like log search, APM trace filtering with duration/status/error queries, smart sampling modes for token efficiency, and cross-correlation between logs, traces, and metrics. Supports both stdio (local) and http (remote/Kubernetes) transports.
Quick Start
Minimal Claude Desktop / VS Code / Cursor config — just the two required keys:
{
"mcpServers": {
"datadog": {
"command": "npx",
"args": ["-y", "datadog-mcp"],
"env": {
"DD_API_KEY": "your-api-key",
"DD_APP_KEY": "your-app-key"
}
}
}
}
With optional tuning (EU site, custom default limits, longer log windows):
{
"mcpServers": {
"datadog": {
"command": "npx",
"args": ["-y", "datadog-mcp"],
"env": {
"DD_API_KEY": "your-api-key",
"DD_APP_KEY": "your-app-key",
"DD_SITE": "datadoghq.eu",
"MCP_DEFAULT_LIMIT": "50",
"MCP_DEFAULT_LOG_LINES": "200",
"MCP_DEFAULT_METRIC_POINTS": "1000",
"MCP_DEFAULT_TIME_RANGE": "24"
}
}
}
}
To run as an HTTP server (e.g. inside a container or Kubernetes pod), add transport variables to the same env block:
"env": {
"DD_API_KEY": "your-api-key",
"DD_APP_KEY": "your-app-key",
"MCP_TRANSPORT": "http",
"MCP_PORT": "3000",
"MCP_HOST": "0.0.0.0"
}
Configuration
Required environment variables
DD_API_KEY=your-api-key
DD_APP_KEY=your-app-key
Optional environment variables
DD_SITE=datadoghq.com # Default. Use datadoghq.eu for EU, etc.
# Limit defaults (fallbacks when the AI doesn't specify)
MCP_DEFAULT_LIMIT=50 # General tools default limit
MCP_DEFAULT_LOG_LINES=200 # Logs tool default limit
MCP_DEFAULT_METRIC_POINTS=1000 # Metrics timeseries data points
MCP_DEFAULT_TIME_RANGE=24 # Default time range in hours
# Transport (alternative to CLI flags — useful in Kubernetes)
MCP_TRANSPORT=stdio # stdio | http
MCP_PORT=3000 # HTTP port
MCP_HOST=0.0.0.0 # HTTP host
Optional flags
--site=datadoghq.com # Datadog site (overrides DD_SITE)
--transport=stdio|http # Transport mode (default: stdio)
--port=3000 # HTTP port when using http transport
--host=0.0.0.0 # HTTP host when using http transport
--read-only # Block all write operations
--disable-tools=synthetics,rum,security # Comma-separated list of tools to disable
Transports
| Transport | When to use | Endpoints |
|---|---|---|
stdio (default) | Local MCP clients — Claude Desktop, Cursor, VS Code | n/a (process stdin/stdout) |
http | Remote / container / Kubernetes | POST /mcp · GET /mcp (SSE) · DELETE /mcp · GET /health |
Select with --transport=http or MCP_TRANSPORT=http.
Deployment
Docker
{
"mcpServers": {
"datadog": {
"command": "docker",
"args": [
"run", "-i", "--rm",
"-e", "DD_API_KEY",
"-e", "DD_APP_KEY",
"-e", "DD_SITE",
"ghcr.io/tantiope/datadog-mcp"
],
"env": {
"DD_API_KEY": "your-api-key",
"DD_APP_KEY": "your-app-key",
"DD_SITE": "datadoghq.com"
}
}
}
}
Kubernetes
Use environment variables — not container args — for transport configuration:
env:
- name: DD_API_KEY
value: "your-api-key"
- name: DD_APP_KEY
value: "your-app-key"
- name: MCP_TRANSPORT
value: "http"
- name: MCP_PORT
value: "3000"
- name: MCP_HOST
value: "0.0.0.0"
Note: Kubernetes
args:replaces the entire Dockerfile CMD, causing Node.js to receive the flags instead of your application. Environment variables avoid this issue.
Tools
| Tool | Action | Category | Description | Required Scopes |
|---|---|---|---|---|
monitors | list | Alerting | List monitors with optional filters | monitors_read |
monitors | get | Alerting | Get monitor by ID | monitors_read |
monitors | search | Alerting | Search monitors by query | monitors_read |
monitors | create | Alerting | Create a new monitor; config is validated against a typed schema covering documented options (notifyNoData, renotifyInterval, thresholds, …) — unknown keys surface in warnings. Pass dry_run: true to validate without creating (uses /api/v1/monitor/validate, allowed in read-only mode). | monitors_write |
monitors | update | Alerting | Update an existing monitor; same validated schema as create; partial configs accepted; validation errors short-circuit before any HTTP call as EINVALID_MONITOR_CONFIG: | monitors_write |
monitors | preview | Alerting | Render a monitor template (inline message or by monitor_id/id) with optional context of variables and conditionals. Returns {rendered, variablesUsed, variablesMissing, conditionalsResolved, tagConditionalsResolved}. Supports Datadog Mustache subset: variable substitution + six documented conditionals (is_alert, is_warning, is_no_data, is_recovery, is_alert_to_warning, is_warning_to_alert) + tag conditionals {{#is_match "tag" "val"}}/{{#is_exact_match "tag" "val"}} (and ^ negations); {{#each}}/partials throw EUNSUPPORTED_TEMPLATE_SYNTAX. Read-only. | monitors_read |
monitors | test_notification | Alerting | Known limitation: returns ENOT_SUPPORTED — Datadog has no public REST endpoint for triggering a test notification. Documentation pointer in response. | n/a |
monitors | delete | Alerting | Delete a monitor | monitors_write |
monitors | mute | Alerting | Mute a monitor | monitors_write |
monitors | unmute | Alerting | Unmute a monitor | monitors_write |
monitors | top | Alerting | Top N monitors by alert frequency with real monitor names and context breakdown. WARNING: total_count includes renotifies/re-evaluations (Datadog emits a renotify event every renotify_interval minutes while Alert). For real fires use action=history. | monitors_read |
monitors | history | Alerting | Count and list real state transitions for one monitor over a time window. Filters by transitionType (default ["alert","alert recovery"] — fires+recoveries, excludes renotifies) and optional group. Returns {transitions: [...], count, meta} where count is the number of real transitions (e.g. for one always-Alert burn-rate monitor over 7d: 98 raw events vs 38 real transitions). | monitors_read, events_read |
dashboards | list | Visualization | List all dashboards | dashboards_read |
dashboards | get | Visualization | Get dashboard by ID | dashboards_read |
dashboards | create | Visualization | Create a new dashboard | dashboards_write |
dashboards | update | Visualization | Update a dashboard | dashboards_write |
dashboards | delete | Visualization | Delete a dashboard | dashboards_write |
logs | search | Logs | Search logs with query syntax and filters | logs_read_data, logs_read_index_data |
logs | aggregate | Logs | Aggregate log data with groupBy | logs_read_data |
logs_pipelines | list, get | Logs Config | Inspect log processing pipelines and their processors | logs_read_config |
logs_pipelines | create, update, delete, reorder | Logs Config | Author pipelines and processor chains | logs_write_config |
logs_pipelines | get_order | Logs Config | Read pipeline evaluation order | logs_read_config |
logs_indexes | list, get | Logs Config | Inspect indexes (filter, retention, Flex tier, exclusion filters); create/delete are UI-only per Datadog and not exposed | logs_read_config |
logs_indexes | update, reorder | Logs Config | Update index filter/retention/quota and reorder evaluation | logs_write_config |
logs_indexes | get_order | Logs Config | Read index evaluation order | logs_read_config |
logs_archives | list, get | Logs Config | Inspect log archives (S3 / GCS / Azure destinations); per-provider credential fields are forwarded unchanged | logs_read_archives |
logs_archives | create, update, delete, reorder | Logs Config | Manage archive destinations; destination.type validated against `s3 | gcs |
logs_archives | get_order | Logs Config | Read archive evaluation order | logs_read_archives |
metrics | query | Metrics | Query timeseries data. Response meta includes rollupRequested (parsed from rollup(method, seconds), with methodInferred flag), rollupEffective (interval derived from returned pointlist intervals + deduped intervalsObserved for multi-series), and rollupOverridden: boolean so callers can detect when Datadog silently downsampled. | metrics_read, timeseries_query |
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