"A service for error tracking and performance monitoring" matching MCP servers:

Enables interaction with Google Cloud services including billing cost analysis, log querying, and metrics monitoring through natural language commands. Provides comprehensive tools for managing GCP resources, analyzing costs, detecting anomalies, and retrieving operational insights.

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.

Automates error tracking workflow by finding code owners in Bitbucket, retrieving related pull requests, and creating assigned JIRA tickets for code errors.

Classifies agent errors and provides clear recovery actions (retry, escalate) with configurable categories and strategies, plus MCP tools for direct agent use.

Enables supervised creation of tracking stack resources—WhatConverts accounts/profiles, GA4 properties, and GTM containers—with dry-run-by-default writes, duplicate-name refusal, rate limiting, and an append-only action log.

Enables natural language time tracking through Claude with markdown file storage. Supports multi-company tracking, flexible time parsing, auto-calculated summaries, and commitment warnings all through conversational input.

Analyzes websites like a senior performance engineer and produces prioritized Core Web Vitals recommendations. Provides 16 tools for detailed performance analysis, including Lighthouse, CrUX, WordPress and Cloudflare inspections.

Connects AI agents to live observability stacks including Sentry, GitHub, Vercel, Better Stack, and Cloudflare, enabling end-to-end incident investigation, deployment correlation, root cause analysis, and regression triage.

Enables web performance analysis using Google PageSpeed Insights and Chrome UX Report APIs, providing compact metrics and diagnostics without local browser automation.

An MCP server that enables Claude to learn from user corrections by recording them as persistent rules in CLAUDE.md files. It manages project-specific or global guidelines to ensure the assistant avoids repeating the same mistakes in future sessions.

MCP server for live ship tracking via AIS data. Provides tools to get vessels in an area, live position by MMSI, and AIS coverage checks.

Provides intelligent error detection and debugging capabilities across multiple programming languages with real-time monitoring of build, lint, runtime, console, and test errors. Offers AI-enhanced error analysis with automated resolution suggestions and context-aware debugging.

Generates formatted performance review documents by providing employee details, review period, accomplishments, and improvement areas.

Turns application errors into reviewed pull requests by automating root-cause analysis, Jira ticket creation, local and CI test gates, and GitHub PRs, with a human as the final merge gate.

A MCP server that turns your scattered SEO and analytics data into one clear verdict per URL. Plug it into Claude, Cursor, or any MCP-aware client and ask: "Which three posts should I update this week?" - and get an answer backed by hard numbers.

A high-performance, modular MCP server with safe-by-default profiles, read-only workspace access, search, diagnostics, and benchmarking tools, built with TypeScript and the MCP v2 SDK.

Enables AI agents to perform read-only static analysis of Node.js backend projects, detecting database query anti-patterns, async bottlenecks, connection pooling mistakes, and dependency hygiene issues while returning structured evidence-backed findings.

A production-ready MCP server for Google Tag Manager, GA4 Measurement Protocol, DataLayer schema validation, Meta CAPI auditing, and tracking code snippet generation.

MCP server enabling Claude Code to capture screenshots of Windows applications through WSL2, allowing AI to diagnose UI errors and verify layouts.

MCP server for creating, listing, inspecting, and validating tracking plans for ecommerce and lead-generation businesses, with JSON storage and TypeScript implementation.