Monitoring AI Agent Skills

A native macOS menu bar application for real-time monitoring of Claude AI usage limits English • Español • Français • Deutsch • Italiano • Português • 日本語 • 한국어 Download Latest Release (v2.3.0) macOS 14.0+ (Sonoma) | ~4 MB | Native Swift/SwiftUI | Officially Signed Claude Usage Tracker is a lightweight, native macOS menu bar application that provides real-ti

Design effective KPI dashboards with metrics selection, visualization best practices, and real-time monitoring patterns. Use when building business dashboards, selecting metrics, or designing data visualization layouts.

Build comprehensive ML pipelines, experiment tracking, and model

Build production ML systems with PyTorch 2.x, TensorFlow, and

Create and manage production Grafana dashboards for real-time visualization of system and application metrics. Use when building monitoring dashboards, visualizing metrics, or creating operational observability interfaces.

Expert performance engineer specializing in modern observability,

Build production-ready monitoring, logging, and tracing systems.

You are an error tracking and observability expert specializing in implementing comprehensive error monitoring solutions. Set up error tracking systems, configure alerts, implement structured logging,

Set up Prometheus for comprehensive metric collection, storage, and monitoring of infrastructure and applications. Use when implementing metrics collection, setting up monitoring infrastructure, or configuring alerting systems.

Production-ready patterns for building LLM applications. Covers RAG pipelines, agent architectures, prompt IDEs, and LLMOps monitoring. Use when designing AI applications, implementing RAG, building agents, or setting up LLM observability.

A powerful Model Context Protocol (MCP) server for Docker operations, enabling seamless container and compose stack management through Claude AI. - 🚀 Container creation and instantiation - 📦 Docker Compose stack deployment - 🔍 Container logs retrieval - 📊 Container listing and status monitoring To try this in Claude Desktop app, add this to your claude config files: To install Docker MCP for C

An MCP server for tracking Binance Alpha trades, helping AI agents optimize alpha point accumulation. - Real-time Trade Monitoring: Track buy-side activity for Binance Alpha tokens by Subscribing to on-chain events. - USD-based Metrics: Calculates trade values in USD using real-time prices from the CryptoCompare. - Data Persistence: Maintains trade data in memory, with automatic cleanup of records

Expert DevOps troubleshooter specializing in rapid incident

The local Dynatrace MCP server allows AI Assistants to interact with the Dynatrace observability platform, bringing real-time observability data directly into your development workflow. If you need help, please contact us via GitHub Issues if you have feature requests, questions, or need help. You can add this MCP server to your MCP Client like VSCode, Claude, Cursor, Amazon Q, Windsurf, ChatGPT,

NOTE: This is an unofficial implementation of MCP Server for ZapCap. An MCP (Model Context Protocol) server that provides tools for uploading videos, creating processing tasks, and monitoring their progress through the ZapCap API. - ZapCap API key You can install uv from here: https://docs.astral.sh/uv/ You can get api key from ZapCap API after registation at https://zapcap.ai/ in their platform h

MCP-Dandan is an integrated monitoring service that observes MCP (Model Context Protocol) communications and detects security threats in real time. It features a modern desktop UI built with Electron for easy monitoring and management. Currently, MCP-Dandan is listed in well-known MCP-related open-source collections and can be found in the following repositories: - Awesome MCP Servers – Security -

A Model Context Protocol (MCP) server that identifies resource-intensive processes on macOS across CPU, memory, and network usage. MacOS Resource Monitor is a lightweight MCP server that exposes an MCP endpoint for monitoring system resources. It analyzes CPU, memory, and network usage, and identifies the most resource-intensive processes on your Mac, returning data in a structured JSON format. -

This is the official MCP (Model Context Protocol) server for LG ThinQ devices. This server provides integrated control capabilities including status monitoring, device control, and profile information for various LG ThinQ devices, built on the LG ThinQ API and Python Open SDK. MCP connection method is stdio. - Prerequisites - Quick Start - Detailed Usage - Tool Reference - Device List Query Retrie

Testing and benchmarking LLM agents including behavioral testing, capability assessment, reliability metrics, and production monitoring—where even top agents achieve less than 50% on real-world benchmarks Use when: agent testing, agent evaluation, benchmark agents, agent reliability, test agent.

The CockroachDB MCP Server is a natural language interface designed for LLMs and agentic applications to manage, monitor, and query data in CockroachDB. It integrates seamlessly with MCP (Model Content Protocol) clients, such as Claude Desktop or Cursor, enabling AI-driven workflows to interact directly with your database. - Cluster Monitoring - Database Operations - Table Management - Query Engin

A Model Context Protocol (MCP) server for interacting with Bugsnag. This server allows LLM tools like Cursor and Claude to investigate and resolve issues in Bugsnag. - Organization & Project Navigation: Easily browse your Bugsnag hierarchy - Error & Event Filtering: Find specific issues with powerful filtering options - Detailed Stacktrace Viewing: See formatted stacktraces with source code contex

Enable AI models to interact with a global network measurement platform through natural language. Give network access to any LLM. Globalping is a free, public API that provides access to a globally distributed network of probes for monitoring, debugging, and benchmarking internet infrastructure. With Globalping, you can run network tests (ping, traceroute, DNS, MTR, HTTP) from thousands of locatio

A system monitoring tool that exposes system metrics via the Model Context Protocol (MCP). This tool allows LLMs to retrieve real-time system information through an MCP-compatible interface. This tool provides the following monitoring capabilities: - CPU Information: Usage percentage, core count, and detailed CPU info - Memory Information: Virtual and swap memory usage - Disk Information: Disk usa