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Integratie / Developer Tools & DevOps

Datadog MCP integratie

Investigate Datadog telemetry, incidents, dashboards, and service health.

Over Datadog MCP

Datadog is a monitoring and observability platform for cloud-scale applications and infrastructure. Use it to visualize telemetry, correlate events, and detect incidents quickly.

Alle integraties
Categorie
Developer Tools & DevOps
Verbinding
OAuth
Type
Tool
Acties
370
Tags
library

Voorbeeldprompts

Wat je Growf kunt vragen te doen met Datadog MCP

  • List active incidents for payment-service
  • Show dashboard latency for my service
  • Create incident P1 for database outage

Beschikbare acties

370 acties die je agents kunnen uitvoeren in Datadog MCP

  • Aap get activation options

    Check whether Datadog App and API Protection (AAP) can be enabled for a service via Remote Configuration (RC), with no code changes. Use when the user asks to install, set up, enable, or onboard AAP for a service and environment. Returns a verdict with a recommended navigation action: the Service I…

  • Aap onboarding

    Step-by-step instructions for enabling Datadog App and API Protection (AAP) to monitor and secure your application. AAP detects security threats, vulnerabilities, and attacks in real time by using Datadog tracing libraries for application deployments, the Datadog security processor for Envoy deploy…

  • Add llmobs annotation queue interactions

    Queue traces, sessions, or spans for human review in an annotation queue. This is how findings become review work: use **search_llmobs_spans** or **find_llmobs_error_spans** to identify the traces worth grading, then queue them here. Returns `interactions` — each with the `id` that **upsert_llmobs_…

  • Add llmobs dataset records

    Create records in a dataset. **Two-step**: PREVIEW (`confirmed=false`) → INSERT (`confirmed=true`). - `confirmed=false`: does NOT insert. Validates that the (project_id, dataset_id) pair exists, then returns `AddDatasetRecordsPreview` with the resolved IDs, planned record count, tag union, first-re…

  • Aggregate datadog ci pipeline events

    Aggregate and analyze CI pipeline events to produce statistics, metrics, and grouped analytics. Use it for questions such as average pipeline duration or failed builds per pipeline. For individual event details or error messages, use search_datadog_ci_pipeline_events instead. aggregation is require…

  • Aggregate datadog test events

    Aggregate Datadog test events for reliability, performance, and execution trends. Use search_datadog_test_events for individual event details. aggregation is required and must be one of count, cardinality, avg, sum, min, max, pc50, pc75, pc90, pc95, or pc99. Use cardinality with metric set to a fac…

  • Aggregate dora events

    Aggregate DORA events into scalar values or timeseries using composable queries and formulas. Each query selects a DORA index, optional metric, aggregation, filter, and group_by facets. Use get_dora_fields to discover valid indexes, measures, facets, cardinality fields, and aggregations.

  • Aggregate events

    Aggregate Datadog events to compute counts, sums, averages, min, max, cardinality, and percentiles (P50, P75, P90, P95, P98, P99), with optional grouping by fields or time intervals. Use this for aggregated analysis such as event counts by source, event frequency over time, or grouped summaries acr…

  • Aggregate rum events

    Aggregate Datadog RUM events to compute counts, sums, averages, min, max, cardinality, and percentiles (P50, P75, P90, P95, P98, P99), with optional grouping by fields or time intervals. Use this for aggregated analysis of RUM data such as session counts over time, error counts by page, or p95 load…

  • Aggregate spans

    Aggregate Datadog APM spans to compute counts, sums, averages, min, max, cardinality, and percentiles (P50, P75, P90, P95, P98, P99), with optional grouping by fields or time intervals. Use this for aggregated analysis such as request counts over time, p95 duration by service or resource, or error …

  • Analyse datadog k8s rollout

    Assemble a Kubernetes Deployment rollout in one call: status, progress, timing (ETA while in progress, duration once finished), the new/previous/old ReplicaSet split by revision, and before/after impact series (RED, resource utilization, log counts). Prefer this over stitching together search_datad…

  • Analyze cloud network monitoring

    Queries Cloud Network Monitoring (CNM) data to view network/transport level information. Use to investigate netork latency, packet loss, TCP failed connections, dial timeouts, or spikes in TCP throughput. Each query accepts a 'scope' field to select which slice of CNM data to query: - 'tcp' (defaul…

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