#Observability MCP Servers
Discover 23 MCP servers tagged with Observability on the Vinkius App Catalog.
Prometheus MCP
Monitor your infrastructure with Prometheus. Run PromQL queries, analyze metrics, and manage time-series data directly from your AI agent.
Kibana MCP
Manage Kibana spaces and saved objects. List dashboards, search index patterns, and organize your observability stack directly from any AI agent.
Dagster MCP
Orchestrate data pipelines via Dagster. Monitor jobs, track runs, manage software-defined assets, and audit schedules directly from any AI agent.
Google Cloud Logging Stream MCP
This MCP does exactly one thing: it queries logs using Google Cloud Logging. That's its only function, and nothing else. Incredible for giving your AI secure observability.
Trigger.dev MCP
Equip your AI agent with direct access to Trigger.dev. Manage background jobs, monitor task runs, and inspect workflow executions without opening the dashboard.
Hookdeck MCP
Manage and monitor webhooks with Hookdeck. List connections, create sources, and control event routing directly from your AI agent.
Levo.ai (API Security & Observability) MCP
Secure your APIs via Levo.ai. Audit endpoints, monitor sensitive data (PII/PHI), and manage OWASP vulnerabilities.
Traefik Hub MCP
Cloud-native API Management & Gateway evaluating proxy topologies explicitly running Kubernetes integrations.
Treblle MCP
Monitor, document, and analyze your API traffic in real-time. Ingest request and response data directly into Treblle for instant observability.
Requirement Decomposition Prover MCP
AI generates the happy path but omits error handling, edge cases, security, and observability. The '80% Problem'. This tool forces complete requirement decomposition BEFORE code generation: specify inputs/outputs, map failure modes, cover boundary conditions, validate OWASP, plan logging.
AgentOps (Agent Telemetry and Monitoring) MCP
Monitor and observe your AI agents with AgentOps. Track traces, spans, and project metrics directly from your agent.
AppDynamics (Application Performance Monitor API) MCP
Monitor application performance, business transactions, and infrastructure health rules directly from your AI agent.
Dynatrace (APM and Observability) MCP
Monitor and manage your Dynatrace environment. Query metrics, track problems, manage entities, and automate observability workflows directly from your AI agent.
Highlight (Session Replay & UX) MCP
Streamline observability by ingesting raw logs, OTLP logs, and OTLP traces directly into Highlight for session replay and UX monitoring.
HyperDX (Open Source Observability) MCP
Monitor logs, events, and alerts via HyperDX. Search logs, manage alert rules, and inspect dashboards directly from your AI agent.
Logflare (Log Management Analytics) MCP
Streamline log management and analytics via Logflare. Ingest events, execute ad-hoc SQL queries, and trigger pre-configured endpoints directly from your AI agent.
Logstash (Server-side Log Pipeline API) MCP
Monitor and manage Logstash instances. Check node health, inspect pipeline statistics, and troubleshoot hot threads directly from any AI agent.
Coralogix MCP
Manage observability, logs, and parsing rules via Coralogix. Ingest logs, monitor SLOs, and control Grafana dashboards directly.
Grafana Cloud MCP
Manage Grafana Cloud organizations, instances, and API keys. List stacks, manage users, and orchestrate observability infrastructure from your AI agent.
Sumo Logic MCP
Manage logs, metrics, and collectors via Sumo Logic. Run search jobs, monitor infrastructure, and manage collectors directly from any AI agent.
CTO Architect Prover MCP
An AI proposed Kubernetes for 50 users, says 'use HTTPS' as a security strategy, and plans database migrations during maintenance windows. That is not architecture. That is Resume-Driven Development. This tool forces five CTO-level architectural axes: stack fitness, failure tolerance, security hardening, migration safety, and observability.
Kubernetes Architecture Prover MCP
An AI generated Kubernetes manifests for a payment service. No resource requests or limits. No PodSecurityStandards. Single replica, no PDB. Zero NetworkPolicies. Every pod could reach every other pod. The payment pod got OOM-killed at 3 AM by a logging sidecar with no memory ceiling. This tool forces resource governance, security hardening, reliability design, observability instrumentation, and network restriction on every workload.
Multi-Agent Orchestrator Prover MCP
An AI designed a multi-agent system where agents 'work together seamlessly,' data 'flows naturally between them,' and failures 'self-heal.' Three days later, Agent B crashed and the pipeline froze for 14 hours. No one knew because there was no tracing. That is not orchestration. That is hope with a tech stack. This tool forces five orchestration axes: role boundaries, handoff protocols, failure containment, consensus mechanisms, and distributed tracing.