| amplitude | This tool acts as an analytics assistant for Amplitude, helping set up tracking, identify product opportunities, examine charts, build dashboards, manage experiments, and analyze user and account data. | Monitoring | — |
| dash0 | Instruments Claude Code sessions with OpenTelemetry, recording tool calls, LLM requests, token consumption, and errors as traces sent to Dash0 or other OTel-compatible backends. | Monitoring | Dash0 |
| datadog | A preview plugin that connects Claude Code to Datadog via a preconfigured MCP server, enabling users to query logs, metrics, traces, and dashboards through natural language conversation. | Monitoring | Datadog |
| dynatrace | Provides Dynatrace observability expertise covering DQL query construction, monitoring of applications and infrastructure, log analysis, problem diagnosis, and incident response, integrating with the Dynatrace MCP server for real-time platform data access. | Monitoring | Dynatrace |
| fullstory | Enables Claude to interface with Fullstory, allowing retrieval of behavioral analytics, session replay data, and customer experience insights. | Monitoring | Fullstory |
| grafana-assistant | Provides guidance and standards for building and operating the Grafana Assistant application and its command-line interface. | Monitoring | Grafana |
| grafana-cloud-mcp | A cloud-hosted MCP server that enables AI-assisted observability for Grafana Cloud, requiring no local setup or installation. | Monitoring | Grafana |
| grafana-mcp | MCP server enabling AI assistants to manage Grafana dashboards, datasources, alerting rules, and incident workflows. | Monitoring | Grafana |
| honeycomb | A collection of skills, agents, and workflows supporting Honeycomb observability tasks, including query patterns, production troubleshooting, SLO management, OpenTelemetry instrumentation, and migrating from Beeline, built to work alongside the Honeycomb MCP server. | Monitoring | Honeycomb |
| incident-io | Integrates incident.io with Claude, enabling incident response and investigation, checking on-call schedules and escalations, and creating runbooks, skills, and architecture documentation. Includes the official incident.io MCP server with OAuth authentication on initial use. | Monitoring | incident.io |
| langfuse | A skill set for using Langfuse, an open-source platform that helps engineers trace LLM behavior, manage prompts, and evaluate model performance. | Monitoring | Langfuse |
| langfuse-observability | A plugin that captures Claude Code's traces, spans, and session telemetry, exporting them to Langfuse to support LLM monitoring, debugging, and evaluation. | Monitoring | Langfuse |
| logfire | Enables integration of Logfire observability into Python applications through automatic instrumentation for frameworks and libraries such as FastAPI, httpx, asyncpg, and SQLAlchemy. | Monitoring | Pydantic |
| logrocket | Enables Claude Code to interface with LogRocket, allowing natural-language queries for retrieving session replays, performance metrics, error issues, and user behavior data. | Monitoring | LogRocket |
| mlflow | A skillset for using MLflow to instrument, trace, evaluate, and iteratively refine AI agents, supporting a complete workflow from monitoring through validation. | Monitoring | MLflow Team |
| newrelic | A Claude Code integration that connects to New Relic telemetry, enabling terminal-based APM performance investigation, cloud cost analysis, Kubernetes debugging, NRQL query writing, and alert response. | Monitoring | New Relic |
| noibu | Noibu's plugin links Claude to ecommerce session, error, and conversion data, plus marketing, support, and commerce platforms, enabling revenue-loss detection, cross-platform actions, and automated workflows. | Monitoring | Noibu |
| pagerduty | Analyzes code changes by comparing them to historical incident data, generating PagerDuty-based risk scores to flag deployment risks before shipping. | Monitoring | — |
| posthog | This tool integrates Claude Code with PostHog, enabling direct access to analytics data, feature flags, experiment results, error tracking, and insights. | Monitoring | — |
| rootly | Provides end-to-end incident management covering deployment safety, incident response coordination, on-call scheduling, and post-incident retrospectives. | Monitoring | Rootly |
| sentry | Sentry integration for retrieving error reports and stack traces, searching issues by fingerprint, enabling developers to debug production errors from within their development environment. | Monitoring | — |
| sentry-cli | Enables interaction with Sentry's command-line interface, allowing users to manage and query Sentry data directly from the terminal. | Monitoring | Sentry |