"A tool for finding errors in the console or browser during frontend development" matching MCP servers:

Enables searching and analyzing Kibana logs through Dev Tools console proxy using only Kibana credentials, with tools for overviews, patterns, anomaly explanations, traces, and query DSL access.

Enables AI agents to monitor and debug browser runtime errors, console logs, and page diagnostics in real time via a Chrome extension and local MCP server.

An MCP server for streaming and searching macOS Console.app and iOS device logs, enabling real-time log access and debugging through natural language.

Provides a unified MCP server to interact with multiple middleware (Loki, MySQL, Redis, RocketMQ, Elasticsearch, MongoDB) through a desktop application for connection management and configuration export.

Streams browser DevTools console, network, storage, and performance data to your IDE's AI agent for real-time debugging and analysis.

Enables live tracing and observability of MCP tool calls, persisting execution traces to MongoDB and streaming them in real time to a dashboard.

Records every browser session (screen, DOM, network, console, storage) and enables time-travel debugging to rewind and analyze failures.

Lets an AI assistant inspect a running Google Chrome or Microsoft Edge browser over the Chrome DevTools Protocol, reading console output, network traffic, DOM snapshots, errors, performance metrics, storage, and screenshots. It also supports live event subscriptions, screen-frame streaming, and one-shot export of everything into an offline-readable archive such as HAR, CSV, and a self-contained HTML report.

A Playwright-based MCP server that exposes a live browser as a traceable, inspectable, debuggable and controllable execution environment for AI agents.

MCP server for browser debugging, inspection, and verification that streams console logs, network errors, and user actions into AI coding assistants.

Provides MCP tools to perform Looker health checks (health_pulse, health_analyze, health_vacuum) via the MCP Toolbox connector.

Enables LLMs to interact with Kibana through composable toolboxes for building dashboards, managing data, and handling alerts, among other operations.

Enables AI agents to interact seamlessly with Splunk environments through 20+ tools for search, analytics, data discovery, administration, and health monitoring. Features AI-powered troubleshooting workflows and supports multiple Splunk instances with production-ready security.

A verifying MCP gateway that pins approved tool manifests and skill files to content addresses, blocking tampered descriptions before they reach model context.

An enterprise MCP server scaffold that provides secure, governed access to internal tools through RBAC, audit logging, rate limiting, and prompt-injection boundaries, with a FastAPI control plane and OpenTelemetry observability.

MCP servers for real-time development monitoring and interactive pair programming.

Enables AI coding agents to access live console logs, errors, and network requests from web applications via a local WebSocket connection, without copying data to chat.

Enables AI agents to diagnose Linux server incidents by collecting and structuring system diagnostics from multiple servers via SSH, with tools for finding incident clusters, gathering context (memory, CPU, swap, etc.), and running arbitrary commands.

Enables Claude Code to inspect network traffic, query the DOM, read console logs, and capture WebSocket frames in Firefox.

Lets an assistant read recorded production AI agent runs — steps, model and tool calls with arguments, and outcomes — along with the findings of comparison runs that checked a prompt or model change against those recordings, and verify a signed evidence bundle offline with no account or network. It is strictly read-only: no tool starts a replay or comparison, so nothing can spend money or act without a person deciding.

MITM proxy MCP server that intercepts and verifies AI agent tool calls, detecting fabrication, tracking costs, verifying outcomes, and inferring user satisfaction.

A safety layer and monitoring copilot for AI agents using Splunk MCP, recording tool calls, enforcing policies, and blocking risky actions.

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 system hardware information (CPU, memory, storage, etc.) and system status (OS, network, resource usage) via MCP tools.

A comprehensive Linux system performance profiler with MCP remote invocation support, featuring advanced process profiling and flame graph generation.

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

Enables AI-driven SOC investigations by providing automated Splunk querying, threat intelligence enrichment, and response actions through natural language. Includes tools for IP pivoting, lateral movement detection, and label harvesting.

Enables natural language interaction with Plausible Analytics data to query traffic, visitors, engagement, and more using conversational questions.

A Model Context Protocol server that provides seamless integration with Coroot observability platform, enabling monitoring of applications, analysis of performance metrics, examination of logs and traces, and management of infrastructure through Coroot's comprehensive API.

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.