Monitoring AI Agent Skills

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

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.

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

X (Twitter) data platform skill for AI coding agents. 120 REST API endpoints, 2 MCP tools, HMAC webhooks. Tweet search, user lookup, follower extraction, write actions, monitoring, giveaway draws, trending topics. Reads from $0.00015/call — 33x cheaper than the official X API.

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 Model Context Protocol server implementation for Last9 that enables AI agents to seamlessly bring real-time production context — logs, metrics, and traces — into your local environment to auto-fix code faster. - View demo announcement blog post - Installation - Configuration - Tools Documentation - Development You can connect to Last9 MCP in two ways: This is the easiest and cleanest setup. You

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

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

The implementation of Model Context Protocol (MCP) server for VictoriaMetrics. This provides access to your VictoriaMetrics instance and seamless integration with VictoriaMetrics APIs and documentation. It can give you a comprehensive interface for monitoring, observability, and debugging tasks related to your VictoriaMetrics instances, enable advanced automation and interaction capabilities for e

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

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

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

A Model Context Protocol (MCP) server for shipment tracking api, package monitoring, and logistics management using the TrackMage API. Supports tracking across 1600+ carriers worldwide. - Carrier Support: Track packages across 1600+ carriers worldwide (full list) - Resources: Workspaces, shipments, orders, carriers, tracking statuses - Tools: Create shipments/orders, get shipment checkpoints, carr

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

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

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.

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

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.

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. -

You are a monitoring and observability expert specializing in implementing comprehensive monitoring solutions. Set up metrics collection, distributed tracing, log aggregation, and create insightful da

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

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

Expert database optimizer specializing in modern performance