Monitoring AI Agent Skills

Implement comprehensive observability for service meshes including distributed tracing, metrics, and visualization. Use when setting up mesh monitoring, debugging latency issues, or implementing SLOs for service communication.

A Model Context Protocol (MCP) server for detecting, monitoring, and analyzing potential wildfires globally using multiple data sources including NASA FIRMS, OpenWeatherMap, and Google Earth Engine. This MCP server provides AI assistants with tools to detect and analyze wildfire activity anywhere in the world by integrating real-time satellite data, weather forecasts, air pollution metrics, and ge

A powerful AI-driven Security Operations Center (SOC) Text2SQL framework based MCP Server (Local and Remote) for converting natural language Prompts to SQL queries dynamically, with integrated security threat analysis and monitoring. - Text2SQL Conversion: Convert natural language queries to optimized SQL - Multiple Interfaces: Support for STDIO, SSE, and REST API - Security Threat Analysis: Built

Real-time global intelligence dashboard — AI-powered news aggregation, geopolitical monitoring, and infrastructure tracking in a unified situational awareness interface. Documentation  ·  Releases  ·  Contributing - 500+ curated news feeds across 15 categories, AI-synthesized into briefs - Dual map engine — 3D globe (globe.gl) and WebGL flat map (deck.gl) with 56 map layer type

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

An MCP server that tracks stablecoin peg integrity across multiple blockchains, helping AI agents detect depegging risks before they escalate. - Stability Reports: Generate detailed reports assessing stablecoin peg stability, including maximum deviation and status (Stable, Moderately Stable, Unstable). - Real-Time Price Monitoring: Fetch current prices and calculate peg deviation from $1 for USD-p

A remote Model Context Protocol (MCP) server that connects AI assistants to your crash reporting and real user monitoring data in Raygun through natural language conversations. 📚 Tool Reference • 🚀 Quick Start • 🔑 Get API Token - 🐛 Error Management - Investigate, resolve, and track application errors and crashes with full stack traces and context - 🚀 Deployment Tracking - Monitor releases and

Automate GitLab project management, issues, merge requests, pipelines, branches, and user operations via Rube MCP (Composio). Always search tools first for current schemas.

You are an SLO (Service Level Objective) expert specializing in implementing reliability standards and error budget-based practices. Design SLO frameworks, define SLIs, and build monitoring that balances reliability with delivery velocity.

Build anomaly detection applications with Azure AI Anomaly Detector SDK for Java. Use when implementing univariate/multivariate anomaly detection, time-series analysis, or AI-powered monitoring.

A portable, single-binary system auditing tool for Linux. Like Lynis but faster and smarter. No configuration needed. No dependencies. Just run. - 🔒 Security: Firewall, SSH hardening, SSL/TLS, fail2ban, SUID binaries, open ports - 🚀 Services: Systemd services, web servers, databases, Docker - 💻 Resources: CPU, RAM, disk usage, top processes - 💾 Storage: SMART health, inode usage, filesystem er

Give Claude Code a browser that thinks. An MCP server that connects Claude Code to Perplexity Comet - enabling agentic web browsing, deep research, and real-time task monitoring. Existing web tools for Claude Code fall into two categories, both with limitations: Return static text. No interaction, no login, no dynamic content. Great for quick lookups, but can't navigate complex sites or fill forms

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

Automate Datadog tasks via Rube MCP (Composio): query metrics, search logs, manage monitors/dashboards, create events and downtimes. Always search tools first for current schemas.

AI-powered debugging and inspection for Kubernetes clusters using Inspektor Gadget. - AI-powered interface for Kubernetes troubleshooting and monitoring - One-click Inspektor Gadget deployment and removal - Intelligent output summarization and analysis - Automatic gadget discovery from Artifact Hub 1. Ensure you have Docker and a valid kubeconfig file 2. Configure the MCP server in VS Code (see IN

Automate Supabase database queries, table management, project administration, storage, edge functions, and SQL execution via Rube MCP (Composio). Always search tools first for current schemas.

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.

Calculate portfolio risk metrics including VaR, CVaR, Sharpe, Sortino, and drawdown analysis. Use when measuring portfolio risk, implementing risk limits, or building risk monitoring systems.

Migration monitoring, CDC, and observability infrastructure

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

This skill should be used when users want to train or fine-tune language models using TRL (Transformer Reinforcement Learning) on Hugging Face Jobs infrastructure. Covers SFT, DPO, GRPO and reward modeling training methods, plus GGUF conversion for local deployment. Includes guidance on the TRL Jobs package, UV scripts with PEP 723 format, dataset preparation and validation, hardware selection, cost estimation, Trackio monitoring, Hub authentication, and model persistence.

An enterprise-grade MCP (Model Context Protocol) server for Jenkins CI/CD integration with advanced features including multi-tier caching, pipeline monitoring, artifact management, and batch operations. - Job Management: Trigger, list, search, and monitor Jenkins jobs with folder support - Build Status: Real-time build status tracking and console log streaming - Pipeline Support: Stage-by-stage pi

A VMware ESXi/vCenter management server based on MCP (Model Control Protocol), providing simple REST API interfaces for virtual machine management. - Support for ESXi and vCenter Server connections - Real-time communication based on SSE (Server-Sent Events) - RESTful API interface with JSON-RPC support - API key authentication - Complete virtual machine lifecycle management - Real-time performance

English | 中文 A lightweight JVM monitoring and diagnostic MCP (Multi-Agent Communication Protocol) server implementation based on native JDK tools. Provides AI agents with powerful capabilities to monitor and analyze Java applications without requiring third-party tools like Arthas. - Zero Dependencies: Uses only native JDK tools (jps, jstack, jmap, etc.) - Lightweight: Minimal resource consumption