MCP servers expose databases, files, SaaS, or business operations as standard tools accessible to AI. When choosing a server, it is necessary to verify data permissions, credential storage, input validation, logs, rate limiting, deployment sources, and maintenance activity. Especially, protocol standardization should not overlook third-party code risks.
ScrapeGraphAI is a web data scraping API for the AI era for developers, data teams, and product teams that need structured web data to extract structured data from websites, reducing agents, selectors, and maintenance efforts. It focuses on streamlining the web scraping process into a callable, maintainable data interface, with key capabilities such as providing ScrapeGraphAI V2, eliminating the need for proxies and selectors, API documentation, and startup resources. It's better suited for teams with clear budget and process needs. Note Before Use: Adhere to the target website's terms, robots rules, and data usage authorization before scraping. If you plan to adopt it for a long time, it is recommended to test input lead time, output availability, manual review costs, and permission boundaries with real samples before deciding whether to put it into a fixed process.
ClassroomIO is an open source learning management system with AI support. The homepage of the official website places open source LMS, course management and AI Support in the main functional area at the same time, indicating that the focus of this product is not to make a general AI portal, but to gather the process around specific tasks. It solves the problems of decentralized enterprise training, induction and certification management processes, and inconsistent course organization and learning support tools. For corporate training teams, educational institutions, course operators, and organizations that need to build their own LMS, if they do encounter such problems repeatedly in normal times, ClassroomIO will be easier for them to directly fall into daily work than general-purpose tools.
MuleRun is an online marketplace for AI agents and AI applications, allowing users to select and directly run different agents according to the scene for tasks such as content creation, office efficiency, data, and marketing, just like visiting an app store. MuleRun also provides MuleRun MCP cloud service capabilities, allowing developers to call multiple MCP services using API keys, integrate agent tools into their workflows and products, and bill points based on the call consumption. Through the "release-price-monetize" mechanism, MuleRun also supports creators to put their self-developed agents on the shelves for sale, and continue to obtain real usage data and revenue, making MuleRun an AI Agent Marketplace and MCP platform that takes into account both use and creation.
XiaoZhi AI is an open-source AI hardware project and console service for developers and hardware vendors, focusing on low-latency voice conversations and scalable agent capabilities. Based on the Model Context Protocol (MCP), Xiaozhi AI connects speech recognition, intent understanding, memory and tool calling in series, and adapts to a variety of common chips and development boards, making it convenient and quick to make products such as emotional companionship, smart home control, desktop voice assistants, and in-vehicle robots. Through the Xiaozhi AI console, users can create agents, configure roles and behaviors, and complete device binding and management, making Xiaozhi AI more worry-free from prototyping to mass production access.
HiMCP.ai is an AI tool integration platform focused on Model Context Protocol (MCP), bringing together over 11,000 MCP servers across various fields such as AI inference, content generation, data analysis, and browser automation. The platform provides developers with unified MCP client and server resources, supports seamless integration with mainstream AI assistants such as Claude, Cursor, and Cline, simplifying the discovery, deployment, and invocation process of AI tools. HiMCP.ai connects AI models with external data sources, APIs, and systems through standardized protocols, improving the scalability and collaboration efficiency of AI applications, making it suitable for building RAG systems, automated workflows, and multimodal AI applications.
MCP.so is an MCP (Model Context Protocol) resource hosting platform created by domestic developer idoubi, aiming to help developers and AI application users discover, share, and use various MCP services, thereby enhancing the connectivity and utility of large language models (LLMs). The platform provides a comprehensive list of MCP servers, covering various features such as file system access, database operations, web automation, map services, and more. Users can quickly find the MCP services they need through keyword searches, and support multi-dimensional filtering by function, protocol type, and other dimensions. The platform encourages users to submit their own MCP server projects and participate in discussions and feedback, fostering the common development of the community. MCP.so also recommends a variety of MCP client tools, such as Claude Desktop, Cherry Studio, Cursor, etc., to help users access and use MCP services more conveniently.
API Tracker's MCP Servers page brings together over 100 official and community-released Model Context Protocol (MCP) servers. The page provides presentation tools by category (e.g., database, browser automation, search engine, blockchain, etc.), making it easy for developers to quickly discover and compare contextual services that can be integrated with large language models (e.g., Claude, Cursor, Windsurf, etc.). Each MCP server comes with integration status, documentation, and platform support information to help developers efficiently access external APIs in IDE and AI Agent environments. This catalog is suitable for technical teams seeking high availability, standardized deployment, and rapid tool integration, making it an essential resource for building AI toolchains.
MCP Servers is an open-source server aggregation platform focused on Model Context Protocol (MCP), bringing together thousands of official and community-built MCP servers covering databases, browser automation, cloud services, search engines, communications, file systems, and more. The platform supports seamless integration with AI clients such as Claude, Cursor, VS Code, and Windsurf, helping developers quickly access external tools and data sources for large language models (LLMs). MCP Servers provides standardized interfaces and tool discovery mechanisms, supports local deployment and remote calling, and is suitable for building RAG systems, AI assistants, automated workflows, and other application scenarios, significantly improving the scalability and collaboration efficiency of AI applications.
AIbase is an open-source MCP (Model Context Protocol) resource platform for developers and AI workers, bringing together more than 120,000 MCP server examples from around the world, covering maps (such as Baidu Maps), search (DuckDuckGo, Exa), data storage, browser automation (Playwright, BrowserTools), image and video processing, database connection (MongoDB, PostgreSQL, Supabase), Figma design access, and many other scenarios. The platform provides detailed classification, documentation, ratings, and standardized interface descriptions, and supports Chinese interfaces and community tutorials to facilitate users to search and deploy by tags. AIbase uses WebAssembly sandbox isolation to run MCP services to ensure security and stability, and supports click-and-click deployment between official and community servers, providing a one-stop solution for developers to quickly integrate multiple tool capabilities into AI Agent applications.
Smithery is a Model Context Protocol (MCP) server registration and management platform designed for large language models (LLMs) and agent systems. It offers over 200 open-source MCP tools across GitHub, Google Drive, Slack, PostgreSQL, and more, allowing users to easily integrate into Claude Desktop, Cursor, or custom proxy systems with a single line of code. Smithery supports both on-premises and hosted deployments, ensuring data security and flexibility, and offers a CLI installer and TypeScript SDK to simplify the development process. The platform is committed to accelerating the construction of an agent ecosystem and improving the scalability and utility of AI systems.
MCP-Get is a command-line tool designed specifically for developers, designed to simplify the process of discovering, installing, updating, and managing Model Context Protocol (MCP) servers. With MCP-Get, users can easily integrate large language models like Claude with external services, databases, and APIs, expanding the capabilities of their AI applications. The platform provides a rich MCP server catalog covering various application scenarios, supporting one-click installation and configuration, and improving development efficiency. MCP-Get is committed to building an open and collaborative MCP ecosystem, fostering interoperability and expanded capabilities of AI tools.
Glama MCP is an AI tool integration platform focused on Model Context Protocol (MCP), offering over 5,000 open-source MCP servers covering various contextual services such as file access, database connections, API integration, and more. Users can search, compare, and connect to these servers through a unified interface, expanding the capabilities of AI models for richer contextual interactions. The platform supports a variety of clients and tools, making it suitable for building context-aware AI systems and is widely used in development, office automation, search engines, and data analysis. Glama MCP is committed to simplifying the integration process of AI with external tools and data sources, making AI applications more intelligent and automated.
MCP Server Hub is a platform focused on the discovery and integration of Model Context Protocol (MCP) servers, bringing together a variety of services contributed by the official and community. The platform supports multilingual tools, including databases (e.g., SQLite, PostgreSQL), version control (Git/GitHub/GitLab), browser automation (Puppeteer/Playwright), search (Brave, OpenAPI, ArXiv), and cloud services (Google Drive, Cloudflare, etc.). Users can filter by label, view documentation, deployment capabilities, and use cases to quickly find the right context extension tool for their AI projects. Hub also aggregates community innovation servers (e.g., NLP agent, Kubernetes management) and official implementations to provide developers with efficient and secure one-stop MCP service ecological support. The platform aims to accelerate the integration of AI applications with external resources through a unified catalog, building an open and collaborative MCP network.
Cursor MCP Directory is a Model Context Protocol (MCP) server integration platform designed for developers to extend the capabilities of Cursor AI Programming Assistant. Through this platform, users can install and configure various MCP servers with one click, enabling seamless connectivity with external tools and services such as database management, browser automation, API integration, and more. Cursor MCP Directory simplifies the discovery and deployment of MCP servers by providing an intuitive interface that allows for browsing and searching by category. Developers can also submit their own MCP servers to join the directory and expand the reach of their tools. The platform's launch marks a further openness and diversification of the AI programming assistant ecosystem, providing developers with more robust tool integration capabilities.
The Claude MCP Server Directory is a Model Context Protocol (MCP) server integration platform designed for AI developers and agent systems, designed to extend the capabilities of Claude AI Programming Assistant. Through this platform, users can install and configure various MCP servers with one click, enabling seamless connectivity with external tools and services such as database management, browser automation, API integration, and more. The Claude MCP Server Directory simplifies the discovery and deployment of MCP servers by providing an intuitive interface that allows for browsing and searching by category. Developers can also submit their own MCP servers to join the directory and expand the reach of their tools. The platform's launch marks a further openness and diversification of the AI programming assistant ecosystem, providing developers with more robust tool integration capabilities.
MCP Server Finder is a comprehensive MCP (Model Context Protocol) service catalog platform for developers and AI technicians. It brings together and categorizes more than 1,000 official and community-contributed MCP servers, including databases (e.g., PostgreSQL, MongoDB), browser automation, search engine interfaces, development tools, blockchains, productivity applications, and more. Each server comes with feature descriptions, integration tags, community reviews, and usage examples for quick browsing and comparison. The platform also offers granular filtering capabilities to help users find the most suitable MCP services by purpose, language, platform, and task type. With its vast resource library and structured indexes, MCP Server Finder provides efficient support for building AI applications with external tool connectivity, making it an important entry point for AI engineers to explore and implement AI-tool interaction.
Alibaba Cloud Bailian MCP Marketplace is an open tool marketplace for enterprises and developers, aiming to seamlessly connect large models with external resources through Model Context Protocol (MCP). The platform provides two methods: official hosting and community self-construction, and users can complete service activation or deployment in a few minutes without managing servers. The bazaar has now launched 15 official MCPs, including Alibaba Cloud CloudOps, and showcased 61 community contribution services, covering maps, databases, web crawling, office software and other functions. With the Serverless Function Computing Environment, users can complete the full lifecycle process of tool registration, permission configuration, and integration with AI Agent on the platform, greatly improving the efficiency of agent construction. Bailian MCP Market has built a unified, elastic, and secure MCP application ecosystem, which is an important infrastructure for promoting the efficient integration of AI tool ecosystems.
Composio MCP Servers is a comprehensive catalog of Model Context Protocol (MCP) servers designed to provide developers with a wealth of resources for AI tool integration. The platform includes more than 100 hosted MCP servers, covering major application services such as Gmail, Slack, Notion, GitHub, Salesforce, and more. Each server supports seamless connectivity with large language models (LLMs) through standardized interfaces, simplifying tool calling and context management. Composio provides intuitive browsing and search functions, making it easy for users to quickly find the server they need, and supports one-click integration into AI programming environments such as Claude and Cursor. The platform is dedicated to building an open and collaborative MCP ecosystem, fostering interoperability and expanded capabilities of AI tools.
mcp.run is a Model Context Protocol (MCP) tool platform for developers and AI users, designed to enable AI applications to quickly connect to external tools and services. Users can register and manage a variety of MCP "servlet" components on the platform, which run securely through the WebAssembly sandbox and can be shared across clients such as Claude Desktop, Cursor, and more. mcp.run supports user-built or officially hosted MCP servers, and can achieve single login and multi-scenario reuse through SSO configuration preset tool combinations (profiles), greatly simplifying the tool integration process. The platform provides HTTP-triggered tasks that allow users to define automated workflows in natural language, such as scraping data, sending reports, or collaborating on content, and call them through APIs or scheduling. mcp.run provides free basic credits (such as 1,000 task usages) and supports team collaboration and enterprise deployment, comprehensively covering the use cases of developing, running, and monitoring MCP toolchains, making it easy, secure, and efficient to build, share, and use AI toolsets.
The Baidu MCP (Model Context Protocol) platform is a standardized connection framework launched by Baidu Search AI Open Platform, designed to help large language models (LLMs) seamlessly integrate with external tools and data sources. Through unified protocol specifications, the platform enables AI models to call various external resources such as search engines, map services, file systems, and databases in a standardized manner, improving the practicability and scalability of the model. Developers can access a large number of available MCP Servers through MCP Plaza, covering multiple fields such as search, map, and file management, and support one-click access and rapid deployment. In addition, as the first large model platform in China to support the MCP protocol, Baidu Intelligent Cloud Qianfan Platform provides complete tool development and service integration capabilities to help developers efficiently build intelligent applications.
PulseMCP is an open-source ecosystem platform focused on Model Context Protocol (MCP), bringing together over 4,500 MCP servers and nearly 300 MCP clients, covering various AI tools such as database access, browser automation, file system operations, time processing, design tool integration, and more. The platform provides unified search, filtering, and integration capabilities to enable developers to quickly discover and connect to the MCP services they need. PulseMCP also provides official SDKs (TypeScript, Python, Java, Kotlin) and documentation to help developers build and deploy MCP-compliant AI applications. Through standardized protocols, PulseMCP aims to enhance the scalability and collaboration efficiency of AI systems, facilitating seamless integration of AI with external tools and data sources.
MCP Servers Hunt is a discovery platform that brings together and showcases high-quality Model Context Protocol (MCP) servers, similar to the "Product Hunt" of AI. It lists several examples of MCP services from official and community sources, including different types of integrations like Cloudflare, Raygun, Neon, Tinybird, Spotify, MySQL, BigQuery, Playwright, AWS, and more. Users can browse through lists, filter features, and performance metrics through intuitive pages, quickly selecting the MCP service that suits their AI application needs. The platform simplifies the process from discovery and deployment to using MCP tools, providing a one-stop entry point for MCP server resources for developers, system administrators, and tech enthusiasts, helping to accelerate the connection and efficiency of AI to external resources.
Portkey MCP Servers is a comprehensive catalog of Model Context Protocol (MCP) servers designed to provide developers with a wealth of resources for AI tool integration. The platform includes more than 40 MCP servers, covering data storage, cloud infrastructure, development tools, content search, AI memory, productivity applications, and more. Each server supports seamless connectivity with large language models (LLMs) through standardized interfaces, simplifying tool calling and context management. Portkey provides intuitive browsing and search functions, making it easy for users to quickly find the server they need, and supports one-click integration into AI programming environments such as Claude and Cursor. The platform is dedicated to building an open and collaborative MCP ecosystem, fostering interoperability and expanded capabilities of AI tools.
ModelScope MCP is a model contextual protocol platform launched by the Alibaba Cloud Magic Community, aiming to establish a standardized connection interface between large language models (LLMs) and external tools and data sources. The platform enables AI models to access and call external services such as search engines, maps, file systems, etc. in a unified manner through the MCP protocol, enhancing the utility and scalability of the model. Currently, ModelScope MCP has launched nearly 1,500 MCP services, covering many popular fields such as search, maps, file systems, and developer tools. The platform also provides an MCP lab to support developers to quickly test and integrate MCP services, lowering the development threshold and accelerating the construction and deployment of AI applications.