Netdata is an open-source real-time infrastructure monitoring platform that provides second-level metric collection, visualization, machine learning-driven anomaly detection, and automated alerts. It can achieve full-stack monitoring without complex configuration.

Binance Alpha MCP is a server for tracking Binance Alpha trades, helping AI agents optimize Alpha point accumulation. It provides real-time trading monitoring, USD-denominated metrics, data persistence, and MCP tools, including functions to get top tokens and trading statistics.

Prometheus MCP Server is a protocol server that enables seamless docking between AI assistants and the Prometheus monitoring system. It supports querying, analyzing, and discovering monitoring metrics in natural language and is compatible with multiple development tool clients.

An advanced Proxmox Model Context Protocol (MCP) server based on Python, providing a rich set of Proxmox tools, including discovery, lifecycle management, network configuration, snapshot/backup, monitoring metrics, resource pool/permission management, and orchestration functions.

An MCP server designed for the Prometheus database, supporting functions such as LLMs retrieving and analyzing metric data through tool functions, searching for metric usage, and executing complex queries.

The Last9 MCP Server is a server implementing the Model Context Protocol, providing local integration of real - time production environment data (logs, metrics, traces) for AI developers to help quickly and automatically fix code.

A service that provides a Model Context Protocol (MCP) interface for Prometheus, supporting the execution of PromQL queries, exploration of metric data, and providing authentication and containerized deployment support.

An MCP server based on TypeScript, providing API interfaces for interacting with Prometheus metric data, and realizing the bridge function between Claude and the Prometheus server.

The Dynatrace Managed MCP server is an open-source project that allows AI assistants to interact with self-hosted Dynatrace Managed deployments through the Model Context Protocol (MCP), directly integrating observability data into AI-assisted workflows. It supports local and remote modes, can be configured for multiple environments, and provides the ability to query data such as problems, security, entities, SLOs, events, logs, and metrics.

Kubernetes MCP is a model context protocol server implemented in Go language, specifically designed to interact with Kubernetes clusters. It provides rich Kubernetes resource management functions through the MCP protocol, supports multiple transmission methods, and includes advanced features such as cluster metric monitoring and log analysis.

This project provides a toolset based on the FastMCP framework for obtaining project quality metric data from SonarQube, simplifying the interaction process with the SonarQube API.

ActionsPulse is an MCP server that provides real-time observability of GitHub Actions in the IDE through GitHub Copilot, including DORA metrics, cost analysis, CI/CD health, and security compliance reports, and generates interactive dashboards.

A Prometheus MCP server based on TypeScript, providing an interface for interacting with Prometheus metric data and implementing the bridge function between Claude and the Prometheus server.

Signoz MCP Server is a server tool for interacting with the Signoz monitoring platform, providing various functions such as testing connections, obtaining dashboard data, querying APM metrics, etc., and supporting local development and containerized deployment.

The Datadog MCP Server is an interface service based on the Model Context Protocol, providing functions to interact with the Datadog API, including data access capabilities for monitoring, dashboards, metrics, events, logs, and incident management.

The AI-assisted Insights Agent is an MCP agent that can transform natural language questions into accurate, interpretable, and reproducible data insights. It translates business questions into SQL queries through a natural language interface, provides interpretable results (including query statements, metric definitions, and data quality), and ensures the reproducibility of analysis. It aims to bridge the gap between business questions and data answers, improving the efficiency and transparency of data analysis.

Scout Monitoring MCP is a locally running MCP server that allows AI assistants to access Scout application performance monitoring data through Docker images, including error tracking, performance metrics, and code-level analysis, helping AI directly fix performance issues in the code.

The Mandoline MCP Server is an AI assistant evaluation framework that provides tools for creating custom evaluation metrics, batch scoring, and performance analysis for AI assistants such as Claude and Cursor through the Model Context Protocol, helping AI continuously improve its own performance.

An MCP server that connects to the Adjust API, supporting querying reports, metrics, and performance data

An MCP server designed for Prometheus, enabling LLMs to retrieve and analyze metric data through predefined routes.

The Gigapipe MCP server is a unified interface service for querying Prometheus metrics, Loki logs, and Tempo trace data.

This is an MCP server for the Microsoft Clarity data export API, supporting querying of Clarity analytics data through MCP clients such as Claude, including multi-dimensional filtering and acquisition of multiple metrics.

Omen is an AI code analysis CLI tool that provides codebase context for AI assistants through multiple metrics such as complexity analysis, technical debt detection, dependency graph, and hotspot analysis, helping to predict defects and identify risks.

This is a Metricool API server based on the Multi - Agent Collaboration Protocol (MCP), which allows AI agents to access and analyze social media metrics, advertising campaign data, and support post scheduling in Metricool accounts.

A semantic metrics modeling assistant based on the MCP protocol that helps data teams define, validate, and visualize business metrics through a conversational interface. It provides enterprise-level data persistence, trust scoring, and BI tool integration, reducing cognitive burden and building data trust.

CryptoWeather AI Bitcoin Signal is an AI service that provides real - time bitcoin price predictions through the Model Context Protocol (MCP). It includes functions such as trading advice, performance metrics, and signal analysis, and updates data every hour.

An unofficial MCP server that provides access to the Keywords Everywhere API for SEO research and keyword analysis, supporting functions such as keyword data, related keywords, domain analysis, traffic metrics, and backlink analysis.

An MCP server that provides real-time system information, allowing you to obtain metrics such as CPU, memory, disk, and network. It supports cross-platform operation and can be accessed through a standardized interface.

An MCP server designed for Prometheus, which supports LLMs to retrieve and analyze metric data through tool functions.

The Token Metrics MCP Server provides comprehensive cryptocurrency data, analysis, and insights. It enables real-time market data, trading signals, price forecasts, and advanced analysis through function calls.

CodeRAG is a tool that transforms codebases into intelligent knowledge graphs. It builds a code structure diagram through Neo4J, supports multi - language analysis, provides code quality metrics and AI integration, and helps with code review, architecture analysis, and refactoring.

An MCP server for accessing e-commerce analytics data through the Triple Whale API, providing functions such as blended statistical data, store information, and queries for available metrics and dimensions.

The Allstacks MCP Server is a Model Context Protocol service that provides comprehensive access to the Allstacks API. It supports over 208 tools through HTTP basic authentication, covering 12 categories such as metric analysis, work item management, user teams, organizational projects, dashboards, employee analysis, predictive planning, tag management, alert monitoring, AI intelligence, work packages, and risk management.

The Northbeam MCP Server is a Model Context Protocol service for accessing Northbeam marketing analytics data, providing functions for querying metrics, dimensions, channel performance, cohort analysis, and attribution data.

The New Relic MCP server is an unofficial community project that provides seamless integration with the New Relic observability platform. Query metrics, manage alerts, monitor applications, and interact with the entire observability stack through a unified interface.

The Last9 MCP Server is a service that implements the Model Context Protocol, providing real-time production environment context (logs, metrics, tracing data) for AI agents to help quickly and automatically fix code. It supports multiple IDEs and tools, and provides functions such as exception query, service dependency graph, and log filtering.

The PlainSignal MCP Server is a tool for obtaining analytics data and metrics. It supports integration with clients such as Claude Desktop through the MCP protocol, providing report query and detailed metric retrieval functions.

A Remote Model Context Protocol (MCP) server that connects to the Washington, D.C. Metro (WMATA) API, supporting natural language queries for real-time traffic information, station navigation, trip planning, etc. It can be deployed on Cloudflare Workers.

This is an OpCon automation platform MCP server based on the Model Context Protocol. It automatically generates 257 tools through the OpenAPI specification, provides complete API coverage and a type - safe TypeScript implementation, supports token and username/password authentication, and includes monitoring metrics and development tools.

An MCP server based on TypeScript that provides an API interface for interacting with Prometheus metric data, serving as a bridge between Claude and Prometheus.