"A tool for real-time error detection in web browsers" matching MCP servers:

Relays error logs from other MCP servers when an LLM call fails and the returned error message is unclear, helping the model handle errors more intelligently.

Enables LLM agents to search and analyze Elasticsearch logs for errors, detect recurring patterns, analyze error-rate trends, and retrieve full trace context through MCP tools.

An open-source MCP server that collects errors from browser console and terminal, then uses OpenRouter's free AI models to generate summaries for AI agents.

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.

An MCP server that enables conversational interaction with Wazuh SIEM, allowing users to investigate alerts, hunt threats, tune false positives, edit rules, and run security actions via natural language.

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

Enables agents to inspect localhost web applications through Chrome DevTools Protocol by listing Chrome targets, attaching to a page, capturing and querying network, console, navigation, and WebSocket events, and managing ephemeral sessions.

Enables Claude Desktop to access the hosted Web Speed API through MCP, requiring only an API key for setup.

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.

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.

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

Give your AI ears and eyes and perception

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

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.

MCP server that integrates with VictoriaMetrics vmanomaly API to enable AI-assisted anomaly detection, model management, and configuration generation.

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.

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.

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.