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

A FastMCP server for Cursor platform APIs enabling spend guardrails, cloud agent monitoring, and inter-agent inbox messaging.

AI coding usage analytics — track spend, model usage, and costs across Cursor and Claude Code sessions.

A VSCode and Cursor extension that captures real-time terminal output and exposes it to AI assistants via the Model Context Protocol. It enables agents to proactively monitor logs, command execution, and errors without requiring manual copy-pasting from the user.

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

Terminal\[X]MCP is a Model Context Provider (MCP) server that enables intelligent terminal automation through a multi-agent system with distributed specialized roles for command execution, security validation, and real-time monitoring.

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

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

Enables real-time monitoring of Cursor Pro usage limits and API quotas across different AI services. Tracks Sonnet 4.5, Gemini, and GPT-5 request usage with alerts when approaching subscription limits.

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.

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.

AI development observability platform. It silently captures structured data from vibe coding sessions via MCP and codifies deviation patterns into project rules to make AI write better code. 100% local and zero runtime dependencies.

Enables querying and analysis of container terminal operations including vessel tracking, crane management, and productivity metrics through natural language interactions with a MySQL database.

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.

Provides health checks, binary validation, and auto-repair for MCP configurations in Claude Desktop, Cursor, and Cline.

API documentation drifts away from the running service, so consumers integrate against a contract nobody keeps. Routebase keeps API design, testing, mocking and documentation on one living source of truth, and this MCP server lets AI agents work in that workspace under the permissions of the connected account.

Revnuvo Company Intelligence tells AI agents what changed at a company, with evidence. It observes company websites, technologies, and DNS over time and returns timestamped, confidence-aware changes, signals, and monitoring.

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.

This MCP server lets agents inspect every Model Context Protocol server on the machine, verify tools by running them in a sandbox, and check each call against a human-approved baseline so that changed or newly appeared tools are blocked before they execute. It also surfaces token cost, capability facts, and drift history for each tool entirely locally, without uploading inventory or requiring an account.

Enables MCP clients to triage SOC alerts while enforcing a trust firewall across retrieval, memory, and privileged actions. It exposes tools for alerts, logs, memory, and alert actions, with defenses that refuse risky operations in the presence of attacker-controllable content.