GitHub
Connect AI assistants to GitHub - manage repos, issues, PRs, and workflows through natural language.
Beschreibung vom Entwickler (englisches Original)
Full Datadog API access: monitors, logs, metrics, traces, dashboards, and observability tools
Diese drei werden nie zu einer Punktzahl zusammengefasst: Meinungen, Messungen und Beliebtheit sind verschiedene Dinge.
Für diesen Server haben wir noch keine Zusammenfassung in einfacher Sprache geschrieben. Unten stehen die Fakten, die wir aus der Registry gelesen haben.
Wähle die KI-App, die du nutzt, und kopiere die Einstellungen.
DD_API_KEY, DD_APP_KEY, DD_SITEAls geheim markierte Werte sind Schlüssel zu deinem Konto. Gib sie nie weiter und füge sie nie in einen Chat ein.
Du brauchst
Welche App nutzt du?
Wähle oben deine App. Wir merken sie uns, damit der Button beim nächsten Mal „In … installieren“ anzeigt.
Öffne Claude Desktop → Settings → Developer → Edit Config und füge dies in claude_desktop_config.json ein
{
"mcpServers": {
"datadog": {
"command": "npx",
"args": [
"-y",
"datadog-mcp"
],
"env": {
"DD_API_KEY": "your-value",
"DD_APP_KEY": "your-value",
"DD_SITE": "your-value"
}
}
}
}Führe das in deinem Terminal aus
claude mcp add datadog --env DD_API_KEY=your-value --env DD_APP_KEY=your-value --env DD_SITE=your-value -- npx -y datadog-mcpTrag die leeren Werte ein, bevor du ihn startest.
In .cursor/mcp.json in deinem Projekt oder in ~/.cursor/mcp.json einfügen
{
"mcpServers": {
"datadog": {
"command": "npx",
"args": [
"-y",
"datadog-mcp"
],
"env": {
"DD_API_KEY": "your-value",
"DD_APP_KEY": "your-value",
"DD_SITE": "your-value"
}
}
}
}Dein Browser fragt, ob er die App öffnen darf, dann zeigt die App die Einstellungen und bittet dich um Bestätigung. Schlüsselwerte bleiben leer, damit du sie selbst einträgst.
In .vscode/mcp.json in deinem Projekt einfügen
{
"servers": {
"datadog": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"datadog-mcp"
],
"env": {
"DD_API_KEY": "your-value",
"DD_APP_KEY": "your-value",
"DD_SITE": "your-value"
}
}
}
}Dein Browser fragt, ob er die App öffnen darf, dann zeigt die App die Einstellungen und bittet dich um Bestätigung. Schlüsselwerte bleiben leer, damit du sie selbst einträgst.
Dieser Server läuft auf deinem Computer, und ChatGPT kann sich nur mit Servern im Internet verbinden. Wähle eine andere App.
Deine Auswahl bleibt in einem Cookie auf diesem Gerät; kein Konto nötig.
DD_SITE envDiese Einstellungen werden aus dem Registry-Eintrag des Entwicklers erzeugt. Wenn in der README etwas anderes steht, folge der README.
Läuft auf deinem Computer; die Tool-Liste erscheint nach der Installation in deiner KI-App.
Wir prüfen Informationen, die jeder sehen kann; den Code haben wir nicht gelesen. Checks, die nicht zutreffen, werden nicht mitgezählt. · Geprüft am 7. Nov. 2026
Der Registry-Name wurde mit dem GitHub-Konto tantiope bestätigt, dem das Repo gehört
Dieses Repo haben wir noch nicht von GitHub gelesen
Dieses Repo haben wir noch nicht von GitHub gelesen
Dieser Server läuft auf deinem Computer; es gibt keinen Endpunkt im Internet
Läuft auf deinem Computer und nutzt stattdessen lokale Einstellungen
Läuft auf deinem Computer; Tool-Listen können wir nur von Endpunkten im Internet lesen
Verglichen mit allen aktiven Servern dieser Kategorie in der Registry. Sterne zählen nur, wenn dem Herausgeber das Repo gehört.
Er hat 1 von 1 zutreffenden Basischecks bestanden. Den Code haben wir nicht gelesen. Bevor du einen Schlüssel oder Token hinzufügst, sieh nach, welche Zugriffe der Server verlangt, und nutze einen Schlüssel, der nur die Berechtigungen hat, die du brauchst.
Das musst du eintragen: DD_API_KEY, DD_APP_KEY
Er läuft auf deinem Computer. Deine KI-App startet ihn bei Bedarf, und die Daten laufen nicht über die Server des Entwicklers (außer der Server ruft selbst einen Onlinedienst auf).
Das GitHub-Repo wurde zuletzt – geändert, und die neueste Version (1.0.9) kam vor 11 Monaten in die Registry.
Apps, die MCP unterstützen, etwa Claude Desktop, Claude Code, Cursor und VS Code. Außerdem brauchst du Node.js auf deinem Computer.
In derselben Kategorie: GitHub, Desktop Commander, Cloudflare MCP
Server derselben Kategorie von anderen Entwicklern, sortiert nach Sternen.
So liest du eine Karte:★ GitHub-SterneiDrei Säulen: Bewertungen · Checks · NutzungiAktualisiert = neueste Version in der Registry veröffentlichti
Connect AI assistants to GitHub - manage repos, issues, PRs, and workflows through natural language.
MCP server for terminal commands, file operations, and process management
Cloudflare MCP servers
Unverändert aus dem Repo des Entwicklers übernommen. PopNx MCP hat den Inhalt weder geprüft noch empfiehlt es ihn. HTML, Bilder und Skripte wurden entfernt. Links führen von dieser Website weg.
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.
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" }
DD_API_KEY=your-api-key
DD_APP_KEY=your-app-key
DD_SITE=datadoghq.com # Default. Use datadoghq.eu for EU, etc.
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
MCP_TRANSPORT=stdio # stdio | http MCP_PORT=3000 # HTTP port MCP_HOST=0.0.0.0 # HTTP host
--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
| 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.
{
"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" } } } }
Use environment variables — not container args — for transport configuration:
env:
Note: Kubernetes
args:replaces the entire Dockerfile CMD, causing Node.js to receive the flags instead of your application. Environment variables avoid this issue.
| 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 | azure_storage` before SDK call | logs_write_archives |
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 | ||
metrics | search | Metrics | Search for metrics by name | metrics_read | ||
metrics | list | Metrics | List active metrics | metrics_read | ||
metrics | metadata | Metrics | Get metric metadata | metrics_read | ||
traces | search | APM | Search spans with filters | apm_read | ||
traces | aggregate | APM | Aggregate trace data | apm_read | ||
traces | services | APM | List APM services | apm_service_catalog_read | ||
events | list | Events | List events | events_read | ||
events | get | Events | Get event by ID | events_read | ||
events | create | Events | Create an event | events_read | ||
events | search | Events | Search events with v2 API and cursor pagination. Optional transitionType filter (e.g. ["alert","alert recovery"]) restricts to monitor state-transition events — without it, source:alert includes renotifies. For monitor-specific fires use monitors action=history. Optional timezone adds *Local ISO 8601 siblings to every timestamp. Zero-result responses include a diagnostics array hinting at the cause (UNINDEXED_TAG_PREFIX, NARROW_TIME_RANGE, RESTRICTIVE_SOURCE_FILTER). | events_read | ||
events | histogram | Events | Server-side bucketing of events by hour_of_day, day_of_week, or day_of_month in an IANA timezone (DST-safe via Intl.DateTimeFormat). Accepts the same transitionType filter as search so monitor histograms can exclude renotifies. Cursor-paginates the underlying search; cap at limits.maxEventsForHistogram (default 5000, MCP_MAX_EVENTS_HISTOGRAM env var). When the cap is hit, returns bucketCountIncomplete: true and nextCursor for continuation. | events_read | ||
events | aggregate | Events | Client-side aggregation by monitor_name, source, etc. | events_read | ||
events | top | Events | Top N event groups by count with generic groupBy support (deployments, configs, alerts, etc.). Groups without context tags are included as "no_context" | events_read |
| events | timeseries | Events | Time-bucketed alert
Nur der Anfang wird gezeigt; den Rest findest du im Repo