Real-time, per‑second infrastructure monitoring platform that provides instant insights, auto‑discovery, edge‑based machine‑learning anomaly detection, and lightweight visualizations without requiring complex configuration.

Enables AI agents, assistants, and chatbots to interact with GitHub via natural‑language commands, providing read‑write access to repositories, issues, pull requests, workflows, security data and team activity.

Provides a secure, elastic sandbox environment for executing AI‑generated code with isolated runtimes and sub‑90 ms provisioning.

Provides a self‑hosted web application firewall and reverse‑proxy that filters, monitors, and blocks malicious HTTP/S traffic, protecting web applications from attacks such as SQL injection, XSS, brute‑force, bot abuse, and various code injections.

Connect APIs quickly, run event‑driven automations, and execute custom code in Node.js, Python, Go, or Bash on a hosted platform.

Provides a configurable MCP server that abstracts connection pooling, authentication, observability, and tool management to accelerate development of database‑backed AI tools.

An AI‑powered email assistant that automates inbox management, enabling users to reach inbox zero fast by handling replies, labeling, archiving, unsubscribing, and providing analytics through a plain‑text prompt configuration.

Provides AI assistants with structured access to n8n node documentation, properties, and operations, enabling automated workflow creation, validation, and management.

Specialized servers that expose AWS capabilities through the Model Context Protocol, allowing AI assistants and other applications to retrieve up‑to‑date AWS documentation, manage infrastructure, query services, and perform workflow automation directly from their context.

Arize Phoenix is an open-source AI and LLM observability tool for inspecting traces, managing prompts, curating datasets, and running experiments.

Adds powerful web scraping, crawling, and search capabilities to LLM clients through a Model Context Protocol (MCP) server.

AWS MCP Servers allow AI agents to interact with and manage a wide range of AWS services using natural language commands. They enable AI-powered cloud management, automated DevOps, and data-driven insights within the AWS ecosystem.

Provides a command‑line interface to manage, test, and deploy Firebase projects, covering hosting, databases, authentication, cloud functions, extensions, and CI/CD workflows.

Firecrawl MCP Server is an official Model Context Protocol (MCP) server implementation that integrates with Firecrawl to provide powerful web scraping capabilities to Large Language Models (LLMs). It acts as a bridge between LLMs and the web, allowing them to access and process web content for various tasks.

Build high-quality data visualization apps quickly with low‑code configuration, leveraging Plotly, Dash, and Pydantic while allowing deep customisation through Python, JavaScript, HTML, and CSS.

Provides a remote Model Context Protocol server for the Notion API, enabling OAuth‑based installation and optimized toolsets for AI agents with minimal token usage.

Klavis AI provides open-source Multi-platform Control Protocol (MCP) integrations and a hosted API for AI applications. It simplifies connecting AI to various third-party services by managing secure MCP servers and authentication.

Remote Model Context Protocol endpoints that let AI clients read, process, and act on data across Cloudflare services such as Workers, Radar, Observability, and more.

Provides an AI‑powered i18n toolkit that enables instant localization of web and mobile applications using large language models, with options to bring your own LLM or use the built‑in translation engine.

An AI-driven tool that helps developers create beautiful, modern UI components instantly through natural language descriptions, right in their IDE.

Provides website analytics, uptime monitoring, and server status in a single self‑hosted application.

Provides cloud browser automation capabilities for LLMs, enabling web navigation, interaction, screenshot capture, and data extraction through Browserbase and Stagehand.

Provides a Model Context Protocol server that enables AI assistants to perform real‑time web searches via the Exa AI Search API, with optional company research, LinkedIn lookup, and deep research workflows.

Enables AI assistants to interact directly with Supabase projects, allowing them to query databases, fetch configuration, manage tables, and perform other project‑level operations.

Provides real-time web search capabilities to AI models via the Perplexity Sonar API, enabling seamless integration within the Model Context Protocol ecosystem.

Provides programmatic access to Grafana dashboards, datasources, alerts, incidents, and related operational data through a Model Context Protocol server, enabling AI assistants and automation tools to query and manipulate Grafana resources.

Provides a visual UI inside supported editors to interact with Nx and Lerna workspaces, run generators, view project details, visualize task graphs, and enrich AI assistants with workspace context.

Provides real‑time web access, bypasses geo‑restrictions, handles bot detection, and offers browser automation for LLMs and AI agents via the Model Context Protocol.

Unified GraphQL federation gateway that composes multiple data sources into a single schema, offering governance, analytics, and seamless integration for enterprise APIs.

Enables popular agent frameworks to integrate with Stripe APIs via function calling, providing tools for MCP, Python, and TypeScript.

Provides a semantic memory layer on top of the Qdrant vector search engine, enabling storage and retrieval of information via the Model Context Protocol.

azure-mcp is a server that implements the Model Context Protocol (MCP) to connect AI agents with Azure services. It allows developers to interact with Azure resources like Storage, Cosmos DB, and the Azure CLI using natural language commands within their development environment.