Analytics & Monitoring Servidores MCP

Mcpcap

Enables Large Language Models to read and analyze network packet captures, providing structured JSON responses about network traffic.

Git Forensics

Investigates git repositories to provide detailed insights into history, branch relationships, and development patterns.

USGS Water

Retrieve real-time water data including stream flow, gage height, and temperature from USGS monitoring stations.

Gemini Data Analysis Research

Analyzes data, generates research papers, and automates email delivery using Google's Gemini Flash 2 AI model.

Marketaux

Integrates the Marketaux API to provide comprehensive news search capabilities based on various criteria.

Vero

Provides a modern, open-source analytics stack designed for data-driven organizations.

Health & Fitness Coach

Provides a comprehensive AI-powered fitness tracking application that integrates with intelligent AI assistants via the Model Context Protocol (MCP).

MDF

Provides a Model Context Protocol server for AI assistants to access and analyze ASAM MDF automotive and industrial measurement data.

YC CSS UI

Intelligently debugs and optimizes CSS styles by detecting layout, performance, and compatibility issues.

Video Parser

Analyzes and queries video content using AI vision models and natural language through the Model Context Protocol.

Etherscan V2

Exposes a curated set of Etherscan V2 endpoints as Model Context Protocol (MCP) tools.

Yandex Metrika

Integrates Yandex Metrika analytics data into AI assistants and applications via a Model Context Protocol server.

Liquidity Pools

Track and analyze decentralized exchange liquidity pools for powering intelligent DeFi agents and automated strategies.

Process Intelligence

Provides deep insight into system and running processes, enabling local LLM agents to analyze machine state and offer real-time solutions.

Mempool

Provides real-time Bitcoin blockchain and mempool data to AI clients via the Model Context Protocol.

Auto-Remediation Monitoring

Monitors, diagnoses, and automatically resolves issues in containerized applications using AI-powered incident analysis.

Log Analyzer

Streamlines interaction with log files through a CLI and MCP server, aiding in debugging and monitoring.

Mandoline

Empowers large language models and AI assistants to conduct self-evaluations, critique their performance, and continuously improve through a standardized evaluation framework.

Customized Elasticsearch

Provides a custom Elasticsearch service built on Python, offering tailored data retrieval tools via the FastMCP protocol.

Claude Terminal Monitor

Monitors terminal output in real-time within Claude AI conversations using the Model Context Protocol (MCP).