[Must-have for developers] Summary of MCP server aggregation platform
Master the MCP protocol to make your AI applications smarter and more flexible.
Core content:
1. MCP protocol definition and its importance in AI applications
2. MCP server functions and advantages, and why MCP server is needed
3. Introduction to the characteristics and functions of the four major MCP server aggregation platforms
What is MCP?
The Model Context Protocol (MCP) is an open protocol that sets a standard for applications to provide contextual information to large language models (LLMs). You can think of MCP as a USB-C interface for AI applications - just as USB-C provides a standard interface for devices to connect to peripherals, MCP provides a standardized way for AI models to connect to different data sources and tools.
What is MCP? Please refer to my recent WeChat article:
MCP uses a client-server architecture that allows host applications to connect to multiple servers. This architecture brings several key advantages:
Provides a large number of pre-built integrations that can be used directly by LLM Flexibility to switch between different LLM providers and suppliers Best practices for protecting data in your infrastructure
Why do I need an MCP server?
MCP servers are an integral part of the entire ecosystem. They act as tool providers, providing LLM with various capabilities, such as:
Database access Code Analysis Design Tools Debugging Features File system operations API Integration etc.
To build powerful AI applications, you need to find and use a suitable MCP server. Although some server implementations can be found in the official GitHub repository , as the ecosystem develops rapidly, more and more aggregation platforms begin to provide server discovery and management capabilities.
MCP Server Aggregation Platform
1. Glama.ai
Glama.ai is one of the largest MCP server directories, with over 2,600 servers as of March 2025. Features of the platform include:
Complete search and filter system, supporting multiple sorting methods (relevance, date added, date updated, download volume, etc.) Detailed server classification (development tools, search, monitoring, etc.) Quality rating system, including security, license, and code quality assessments Supports officially certified server logos Provides detailed statistics for each server, such as downloads, GitHub star count, etc.
2. Smithery.ai
Smithery.ai is a professional MCP server discovery and integration platform that provides:
More than 2,600 MCP functions integrated Featured Recommended Server List Detailed usage statistics (such as usage per server) Support icon preview and quick access Full server description and links to documentation
3. MCP.so
MCP.so is a community driven open source MCP server directory platform. While the site may be under construction at the moment, its goals are:
Provides a centralized display of open source MCP servers Support community contributions and collaboration Focus on developer-friendly documentation and examples Simplify the server publishing and sharing process
4. MCPT.com
MCPT.com plans to be a platform focused on enterprise-level MCP server solutions. Although the platform may not be fully online yet, its planned functions include:
Evaluation and comparison of enterprise-level MCP servers Security and compliance certifications Enterprise customized deployment solutions Technical support and consulting services
Summarize
MCP servers are important infrastructure for building modern AI applications. Through these aggregation platforms, developers can more easily discover, evaluate and use various MCP servers. Whether individual developers or enterprise users, they can find solutions that suit their needs.
As the MCP ecosystem continues to grow, these aggregation platforms are also continuously improving and innovating to provide developers with a better server discovery and management experience. It is recommended that developers choose the appropriate platform to find and manage MCP servers based on their specific needs.
