#Observability MCP Servers

Monitor your infrastructure with Prometheus. Run PromQL queries, analyze metrics, and manage time-series data directly from your AI agent.

Manage Kibana spaces and saved objects. List dashboards, search index patterns, and organize your observability stack directly from any AI agent.

Orchestrate data pipelines via Dagster. Monitor jobs, track runs, manage software-defined assets, and audit schedules directly from any AI agent.

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.

Equip your AI agent with direct access to Trigger.dev. Manage background jobs, monitor task runs, and inspect workflow executions without opening the dashboard.

Manage and monitor webhooks with Hookdeck. List connections, create sources, and control event routing directly from your AI agent.

Secure your APIs via Levo.ai. Audit endpoints, monitor sensitive data (PII/PHI), and manage OWASP vulnerabilities.

Cloud-native API Management & Gateway evaluating proxy topologies explicitly running Kubernetes integrations.

Monitor, document, and analyze your API traffic in real-time. Ingest request and response data directly into Treblle for instant observability.

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.

Monitor and observe your AI agents with AgentOps. Track traces, spans, and project metrics directly from your agent.

Monitor application performance, business transactions, and infrastructure health rules directly from your AI agent.

Monitor and manage your Dynatrace environment. Query metrics, track problems, manage entities, and automate observability workflows directly from your AI agent.

Streamline observability by ingesting raw logs, OTLP logs, and OTLP traces directly into Highlight for session replay and UX monitoring.

Monitor logs, events, and alerts via HyperDX. Search logs, manage alert rules, and inspect dashboards directly from your AI agent.

Streamline log management and analytics via Logflare. Ingest events, execute ad-hoc SQL queries, and trigger pre-configured endpoints directly from your AI agent.

Monitor and manage Logstash instances. Check node health, inspect pipeline statistics, and troubleshoot hot threads directly from any AI agent.

Manage observability, logs, and parsing rules via Coralogix. Ingest logs, monitor SLOs, and control Grafana dashboards directly.

Manage Grafana Cloud organizations, instances, and API keys. List stacks, manage users, and orchestrate observability infrastructure from your AI agent.

Manage logs, metrics, and collectors via Sumo Logic. Run search jobs, monitor infrastructure, and manage collectors directly from any AI agent.

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.

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.

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.