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

Provides agents with real Linux VMs to run commands, manage files, expose ports, and track costs, all through an ephemeral sandbox service.

Enables Claude/Lyra to create, monitor, and manage live sessions for long-running operations such as downloads, conversions, and agent jobs, with progress metrics, logs, error alerts, and a Textual dashboard; it also ingests updates from external media-server tools.

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.

Provides over 1,000 creative ways to decline requests across four categories (polite, humorous, professional, and creative). The MCP server wraps a REST API to help users craft professional rejections through natural language interactions.

Cross-chain cryptocurrency swaps via Chainflip. Get quotes, execute swaps, and track progress. No API key required to get started.

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.

An MCP server that enables querying performance review periods, records, details, and saving self-assessment drafts without final submission.

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.

A generic MCP server for tracking any entity type (e.g., weight, workouts, books) without predefined schemas, using SQLite with JSON columns for flexible data storage and querying.

Governs and automates network monitoring across SolarWinds Orion and Paessler PRTG platforms with a unified MCP server, enabling querying, alert management, and governed writes with audit logging.

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

Explains known developer errors offline and deterministically (CORS, ESM/CommonJS, npm ERESOLVE, Next.js builds, Postgres connection and DATABASE_URL errors). One tool, explain_error; no LLM, no network.

Multi-carrier parcel tracking server that communicates directly with carrier APIs (DHL, UPS, FedEx, etc.) without third-party aggregators, providing normalized tracking status and events.

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.

Enables comprehensive analysis of AWS Lambda performance including cold start tracking, memory utilization monitoring, cost analysis, and optimization recommendations. Provides real-time metrics, comparative analysis across multiple functions, and actionable insights to improve Lambda performance and reduce costs.

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.