"Reading terminal outputs from a Next.js dev server while developing in Cursor" matching MCP servers:

Enables AI agents to monitor Docker containers, system resources, ports, and logs in real-time.

MCP server that wraps Cursor Enterprise API to enable AI agents to answer questions about team spending, usage, and model adoption.

Query Grafana logs, metrics, and dashboards from Cursor. Enables the AI to call your Grafana instance via tools without leaving the editor.

An MCP server for Updown.io that enables managing website monitoring checks, viewing downtimes and metrics, configuring alert recipients, and controlling status pages through natural language.

Um servidor MCP completo para integração com Sentry no Cursor, oferecendo 27 ferramentas para monitoramento de erros, performance e saúde de aplicações.

An MCP server on AWS Lambda that gives AI assistants read-only access to SQS dead-letter queues and CloudWatch logs for fast incident triage.

Enables AI agents to push and read metrics from EzStat, track counters/gauges, and ask natural-language questions about telemetry.

An MCP server that provides cost and reliability observability for LLM and agent workflows. It records model calls and allows querying and aggregating telemetry data through MCP tools.

Enables Claude to discover and understand infrastructure-as-code drift by listing projects with drift, analyzing Terraform plan outputs, and providing remediation information.

MCP server for inspecting IBM Liberty/WebSphere application servers over SSH, enabling reading sanitized configs, performing health checks, and searching logs remotely.

An MCP server that enables AI agents to safely operate multi-cluster Kubernetes fleets through an Open Cluster Management hub, with policy enforcement, human approval, and audit tracing.

MCP server for Loggy that enables AI coding assistants to manage heartbeats, status pages, uptime monitors, feature flags, and logs via natural language.

Enables AI assistants to query and analyze AI agent sessions from observability providers like Shepherd (AIOBS) and Langfuse, allowing users to debug agent runs, compare sessions, track performance, and analyze LLM usage patterns.

SuperDev is a local-first desktop app + MCP server that gives AI coding agents (Claude Code, Codex, Cursor — anything MCP-compatible) access to the runtime: live and historical logs across services, breakpoints in already-running processes (same PID, no restart), real browser control, and DAG deploy pipelines — with human approval and an audit trail on protected writes.

Enables interaction with Datadog's monitoring platform to search logs, search trace spans, and perform trace span aggregation for analysis.

Read-only MCP server for TrueNAS Scale debugging, providing k3s tools for kubectl operations and whitelisted midclt calls for system info, apps, and pools.

A read-only MCP server that exposes Azure incident-investigation tools for a single App Service and its Application Insights telemetry, enabling an agent to correlate deployment history, platform metrics, and transaction traces.

Gives AI agents real-time access to system metrics, process management, and container orchestration.

Enables querying and managing AI logs through tools like listing logs, retrieving jobs, and performing AI-powered chat queries. Also provides access to gateway security reports and guardrail testing.

A Model Context Protocol server that provides comprehensive tools for monitoring and identifying performance bottlenecks in Logstash instances through an interactive web UI and JSON-RPC interface.