Overview and Comparison of Platforms for MCP (Model Context Protocol) Servers
Contents
- Introduction to MCP (Model Context Protocol)
- Categories of Platforms for MCP Servers
- Overview of Key Platforms for MCP Servers
- Marketplaces and Registries of MCP Servers
- MCP Servers with Authentication Support
- Comparative Table of Platforms for MCP Servers
- Popular MCP Servers and Their Comparison
- Recommendations for Choosing a Platform
- Trends in the Development of MCP Platforms
- Frequently Asked Questions About MCP Platforms
- Resources for Learning MCP
- Concluding Recommendations
Introduction to MCP (Model Context Protocol)
Model Context Protocol (MCP) is an open protocol that standardizes interaction between applications and language models (LLM), such as Claude from Anthropic. Introduced in late 2024, MCP allows AI assistants to access external data, tools, and APIs through a standardized interface.
Figuratively speaking, MCP can be compared to a USB port for AI applications. It allows AI models to securely interact with local and remote resources – from the file system and databases to external APIs and services.
MCP servers are programs that implement the MCP protocol and provide tools, resources, and prompts for AI clients. They can provide access to various data sources (files, documents, databases) and APIs, expanding the capabilities of AI systems.
Categories of Platforms for MCP Servers
Based on the conducted research, four main categories of platforms related to MCP can be distinguished:
- Development Frameworks - libraries and tools for creating MCP servers
- Registries and Catalogs - platforms for finding and installing ready-made MCP servers
- Hosting Platforms - services for hosting and managing MCP servers
- Management Tools - applications for installing and administering MCP servers
Overview of Key Platforms for MCP Servers
1. Frameworks for Developing MCP Servers
EasyMCP (TypeScript)
EasyMCP offers the simplest possible approach to creating MCP servers with a minimum of code. The developer does not need to worry about the details of the protocol implementation.
Key Features:
- Express-like API for defining tools and resources
- Automatic parameter definition using decorators
- Context object for logging
Pros:
- Minimal amount of code to launch the server
- Simple and understandable for TypeScript developers
- Good typing for early error detection
Cons:
- As of early 2025, still in beta
- Lack of support for some advanced MCP features
- No explicit plugin or middleware system
Ideal for: rapid prototyping, hackathons, demos, or integrating quick tools into an AI assistant.
FastAPI-MCP (Python/FastAPI)
FastAPI-MCP is an extension of the popular FastAPI web framework that automatically exports existing REST API endpoints as MCP tools.
Key Features:
- "Zero configuration" for integration with FastAPI
- Automatic discovery of all existing API endpoints
- Reuse of Pydantic schemas for input data validation
Pros:
- Exceptional simplicity for FastAPI users
- Reuse of FastAPI authentication, middleware, and error handling
- Good performance thanks to FastAPI/Uvicorn asynchronicity
Cons:
- Only useful if you are already using FastAPI
- Limited by FastAPI paradigms
- Automatically exposing all endpoints may be too permissive
Ideal for: Python developers who want to quickly integrate an existing API with AI agents without rewriting code.
FastMCP (TypeScript)
FastMCP is a full-featured TypeScript framework with a rich set of ready-made functions and a simple API.
Key Features:
- Support for authentication, user sessions, structured logging
- SSE streaming, progress notifications, sampling support
- CLI tool for development and testing
Pros:
- Good balance between simplicity and power
- Declarative API for quickly creating servers
- Support for advanced MCP features
Cons:
- Higher learning curve due to the large number of functions
- Inherits Node.js limitations in terms of performance
- Requires understanding of several transport protocols
Ideal for: creating production servers in TypeScript that may require data streaming, multi-step interactions, or user sessions.
MCP-Framework (TypeScript)
MCP-Framework focuses on rapid development with a CLI for project creation and automatic component discovery.
Key Features:
- CLI for project creation (
mcp create) - Automatic discovery of tools/resources from code
- Support for multiple transports (stdio, SSE, HTTP stream)
Pros:
- Very quick start thanks to CLI
- Minimum manual configuration
- Active community with Discord support
Cons:
- Requires learning framework conventions
- Additional layer of abstraction over MCP SDK
- Average performance (based on Node.js)
Ideal for: developers who want to get started quickly and create a well-structured project from scratch.
Foxy Contexts (Golang)
Foxy Contexts is a Go library with an emphasis on performance and a declarative approach to creating MCP servers.
Key Features:
- Using Uber Fx for dependency injection
- Support for both STDIO and SSE transports
- Testing package (foxytest)
Pros:
- High performance and efficiency of Go
- Clean separation of components thanks to DI
- Excellent scalability
Cons:
- Higher complexity compared to scripting languages
- Smaller community and fewer available materials
- Requires experience with Go and DI patterns
Ideal for: applications requiring high performance, teams with Go experience, servers with expected high load.
2. Registries and Catalogs of MCP Servers
Portkey.ai
https://portkey.ai/mcp-servers
Portkey.ai offers a comprehensive map of all available MCP servers, from reference implementations to community contributions.
Key Features:
- Categorization of MCP servers by category
- Detailed descriptions and links to repositories
- Regular updates to include new servers
Pros:
- Well-structured and easy-to-navigate interface
- Comprehensive overview of the MCP ecosystem
- Inclusion of both official and third-party servers
Cons:
- No direct server installation capability
- Limited information on compatibility and requirements
Ideal for: exploring available MCP server options and choosing the most suitable one for specific needs.
mcp-get.com
mcp-get is a registry of MCP servers with search capabilities and command-line tools for installation and management.
Key Features:
- Server search with filtering
- Command-line tool for installing servers
- Ratings and reviews from the community
Pros:
- Direct integration with the installation tool
- Usage analytics and statistics
- Active user community
Cons:
- Not as extensive a catalog as some competitors
- Limited support for some operating systems
Ideal for: developers who want to quickly find and install MCP servers via the command line.
mcp.so
mcp.so is an extensive catalog of MCP servers with detailed documentation and installation instructions.
Key Features:
- Extensive collection of servers (thousands of options)
- Categorization and tags for easy searching
- Detailed server pages with usage examples
Pros:
- One of the most complete catalogs of MCP servers
- Active community and regular updates
- Detailed documentation for each server
Cons:
- No integrated tools for server management
- It can be difficult to find what you need due to the large number of options
Ideal for: discovering specialized MCP servers for specific tasks, exploring the capabilities of the MCP protocol.
mcpm.sh
mcpm.sh (MCP Manager) is an open-source service and command-line tool for managing MCP servers in the style of Homebrew.
Key Features:
- Managing server configurations through multiple clients
- Automatic server updates
- Router for connecting to multiple servers
Pros:
- Ease of installation and use
- Dependency and version management
- Support for both local and remote servers
Cons:
- Smaller catalog compared to some alternatives
- Primarily aimed at experienced command-line users
Ideal for: developers who want to manage multiple MCP servers uniformly in the style of package managers.
3. Hosting Platforms for MCP Servers
mcp.run
mcp.run is a hosting platform that provides a registry and control plane for installing and running secure and portable MCP servers.
Key Features:
- Centralized hosting of MCP servers
- Access and security management
- Scaling and monitoring
Pros:
- Simplified server deployment
- Centralized management
- Ensuring security and isolation
Cons:
- Potential dependence on a third-party service
- Possible restrictions for server configuration
Ideal for: organizations that require centralized and secure deployment of MCP servers without the need for their own infrastructure.
Composio
Composio offers over 100 managed MCP servers with built-in authentication and easy connectivity.
Key Features:
- Ready-to-use managed MCP servers
- Built-in authentication and security
- Seamless scaling
Pros:
- Eliminating the need to configure servers
- High availability and performance
- Professional support
Cons:
- May be more expensive than self-hosting
- Limited control over infrastructure
Ideal for: enterprises and teams that need quick access to reliable MCP infrastructure without technical complexities.
Cloudflare for MCP
https://blog.cloudflare.com/remote-model-context-protocol-servers-mcp/
Cloudflare offers the ability to create and deploy remote MCP servers using its infrastructure.
Key Features:
- Integration with Cloudflare Workers
- Global network with low latency
- Security and scalability
Pros:
- Using the Cloudflare global network
- Integration with other Cloudflare services
- High performance and availability
Cons:
- Binding to the Cloudflare ecosystem
- Potentially complex setup for beginners
Ideal for: developers already using Cloudflare and teams needing globally distributed MCP servers with high performance.
MCPServer.cloud
MCPServer.cloud is a hosting platform specializing in hosting and managing MCP servers in the cloud.
Key Features:
- Fast deployment of MCP servers in the cloud
- Control panel for monitoring and control
- Highly available infrastructure
Pros:
- Ease of scaling
- No need to configure your own infrastructure
- Automatic updates
Cons:
- Limitations on customization options
- Potential dependence on the provider
Ideal for: teams that need to quickly deploy an MCP server without delving into infrastructure details.
4. MCP Server Management Tools
mcp-cli
https://github.com/wong2/mcp-cli
mcp-cli is a command-line inspector for the MCP protocol, allowing you to explore and debug servers.
Key Features:
- Interactive mode for testing servers
- Support for various transport protocols
- Detailed information about available tools and resources
Pros:
- Convenient for development and debugging
- Easy-to-use command-line interface
- Support for advanced MCP features
Cons:
- Limited functionality for mass management
- Primarily aimed at developers
Ideal for: MCP server developers who need a tool for testing and debugging.
MCPHub
https://github.com/Jeamee/MCPHub-Desktop
MCPHub is an open-source application for macOS and Windows for discovering, installing, and managing MCP servers.
Key Features:
- Graphical interface for managing servers
- Server discovery and installation
- Status and log monitoring
Pros:
- Friendly user interface
- Simplified management of multiple servers
- Open source
Cons:
- Limited support for some specialized servers
- Fewer customization options compared to CLI tools
Ideal for: users who prefer a graphical interface for managing MCP servers and those new to the MCP ecosystem.
mcp-guardian
https://github.com/eqtylab/mcp-guardian
mcp-guardian is a GUI application and tools for proxying and managing MCP servers.
Key Features:
- Centralized access management
- Proxying requests to servers
- Monitoring and logging
Pros:
- Improved security and control
- Easy addition and management of servers
- Flexible configuration
Cons:
- Additional level of complexity
- Requires separate configuration
Ideal for: organizations with high security requirements and the need for centralized control over MCP servers.
Marketplaces and Registries of MCP Servers
GitHub (modelcontextprotocol/servers)
https://github.com/modelcontextprotocol/servers
The official MCP server repository contains reference implementations and links to servers created by the community.
Key Features:
- Reference implementations of servers for various use cases
- Documentation and implementation guidelines
- Support from the main developers of the MCP protocol
Pros:
- Official source with high code quality
- The most up-to-date and specification-compliant servers
- Detailed documentation and examples
Cons:
- Aimed at developers familiar with GitHub
- No centralized GUI for management
Ideal for: developers who want to study reference implementations and follow best practices.
Glama.ai
Glama.ai provides a catalog of ready-to-use and experimental MCP servers with an emphasis on expanding AI capabilities.
Key Features:
- Extensive collection of servers for various tasks
- Emphasis on innovative applications of MCP
- Integration with other Glama services
Pros:
- Simple, well-organized interface
- Detailed descriptions of the capabilities of each server
- Active developer community
Cons:
- Some servers may be experimental
- Not all servers have equally detailed documentation
Ideal for: innovators exploring new ways to interact AI with external data and tools.
Smithery.ai
Smithery.ai is a registry of MCP servers that helps you find the right tools for AI agents.
Key Features:
- Intelligent search and recommendations
- Emphasis on user experience and ease of search
- Integration with various LLM agents
Pros:
- Intuitive interface for searching and filtering
- Detailed profiles of each server with usage examples
- User ratings and reviews
Cons:
- Smaller collection compared to some other catalogs
- Focused more on end users than developers
Ideal for: AI users looking for specific tools to enhance the capabilities of their AI assistants.
MCP Servers with Authentication Support
Pipedream MCP
Pipedream MCP offers MCP servers with built-in authentication, integrated with the Pipedream platform for automation.
Key Features:
- Secure authentication for accessing MCP servers
- Integration with the Pipedream ecosystem
- Automation of workflows via MCP
Pros:
- Enterprise-grade security
- Easy integration with other services via Pipedream
- Advanced logging and auditing capabilities
Cons:
- Requires familiarity with the Pipedream platform
- Potential limitations of the free plan
Ideal for: business users who need secure AI integration with existing workflows.
Composio MCP with Authentication
Composio MCP provides over 100 managed MCP servers with built-in authentication and security.
Key Features:
- Various authentication methods (API keys, OAuth)
- Access rights management at the server and tool level
- Specialized MCP servers for enterprise clients
Pros:
- Ready-to-use servers without complex configuration
- Compliance with corporate security standards
- Centralized access management
Cons:
- Paid plans for advanced features
- Binding to the Composio infrastructure
Ideal for: organizations requiring secure and managed access to MCP servers with minimal setup effort.
Comparative Table of Platforms for MCP Servers
Development Frameworks
| Framework | Language | Ease of Use | Functionality | Extensibility | Performance | Community | Features |
|---|---|---|---|---|---|---|---|
| EasyMCP | TypeScript | ⭐⭐⭐⭐⭐ | ⭐⭐⭐ | ⭐⭐ | ⭐⭐⭐ | ⭐⭐ | Maximum simplicity, decorators |
| FastAPI-MCP | Python | ⭐⭐⭐⭐⭐ | ⭐⭐⭐⭐ | ⭐⭐⭐ | ⭐⭐⭐ | ⭐⭐⭐⭐ | FastAPI integration, endpoint auto-discovery |
| FastMCP | TypeScript | ⭐⭐⭐⭐ | ⭐⭐⭐⭐⭐ | ⭐⭐⭐⭐ | ⭐⭐⭐ | ⭐⭐⭐⭐ | Full-featured, CLI, sessions |
| MCP-Framework | TypeScript | ⭐⭐⭐⭐⭐ | ⭐⭐⭐⭐ | ⭐⭐⭐⭐ | ⭐⭐⭐ | ⭐⭐⭐ | CLI project creation, auto-discovery |
| Foxy Contexts | Go | ⭐⭐⭐ | ⭐⭐⭐⭐ | ⭐⭐⭐⭐ | ⭐⭐⭐⭐⭐ | ⭐⭐ | DI, high performance |
Registries, Marketplaces, and Platforms
| Platform | Type | Number of Servers | Ease of Use | Management | Documentation | Integration | Authentication |
|---|---|---|---|---|---|---|---|
| Portkey.ai | Catalog | ⭐⭐⭐⭐ | ⭐⭐⭐⭐ | ⭐⭐ | ⭐⭐⭐⭐ | ⭐⭐⭐ | ⭐⭐ |
| mcp-get.com | Registry+CLI | ⭐⭐⭐ | ⭐⭐⭐⭐ | ⭐⭐⭐⭐ | ⭐⭐⭐ | ⭐⭐⭐⭐ | ⭐⭐ |
| mcp.so | Catalog | ⭐⭐⭐⭐⭐ | ⭐⭐⭐⭐ | ⭐⭐ | ⭐⭐⭐⭐⭐ | ⭐⭐⭐ | ⭐⭐ |
| mcpm.sh | Package manager | ⭐⭐⭐ | ⭐⭐⭐⭐ | ⭐⭐⭐⭐⭐ | ⭐⭐⭐ | ⭐⭐⭐⭐ | ⭐⭐⭐ |
| mcp.run | Hosting | ⭐⭐⭐ | ⭐⭐⭐⭐ | ⭐⭐⭐⭐⭐ | ⭐⭐⭐ | ⭐⭐⭐⭐ | ⭐⭐⭐⭐ |
| Composio | Hosting | ⭐⭐⭐⭐ | ⭐⭐⭐⭐⭐ | ⭐⭐⭐⭐⭐ | ⭐⭐⭐⭐ | ⭐⭐⭐⭐ | ⭐⭐⭐⭐⭐ |
| Cloudflare | Hosting | ⭐⭐⭐ | ⭐⭐⭐ | ⭐⭐⭐⭐ | ⭐⭐⭐⭐ | ⭐⭐⭐⭐⭐ | ⭐⭐⭐⭐ |
| MCPServer.cloud | Hosting | ⭐⭐⭐ | ⭐⭐⭐⭐ | ⭐⭐⭐⭐ | ⭐⭐⭐ | ⭐⭐⭐ | ⭐⭐⭐⭐ |
| Glama.ai | Catalog | ⭐⭐⭐⭐ | ⭐⭐⭐⭐ | ⭐⭐⭐ | ⭐⭐⭐⭐ | ⭐⭐⭐ | ⭐⭐ |
| Smithery.ai | Registry | ⭐⭐⭐ | ⭐⭐⭐⭐⭐ | ⭐⭐⭐ | ⭐⭐⭐ | ⭐⭐⭐ | ⭐⭐ |
| Pipedream MCP | Hosting | ⭐⭐⭐ | ⭐⭐⭐⭐ | ⭐⭐⭐⭐ | ⭐⭐⭐ | ⭐⭐⭐⭐⭐ | ⭐⭐⭐⭐⭐ |
Popular MCP Servers and Their Comparison
Based on the materials studied, here is a comparison of the 10 most popular MCP servers:
| Server | Purpose | Features | Ease of Use | Popularity |
|---|---|---|---|---|
| File System MCP | File operations | Access to the local file system | ⭐⭐⭐⭐⭐ | ⭐⭐⭐⭐⭐ |
| GitHub MCP | Code management | Repository management, PRs, issues | ⭐⭐⭐⭐ | ⭐⭐⭐⭐⭐ |
| Slack MCP | Communications | Automation of messages and channels | ⭐⭐⭐⭐ | ⭐⭐⭐⭐ |
| Google Maps MCP | Geodata | Place search, routes, geocoding | ⭐⭐⭐⭐ | ⭐⭐⭐⭐ |
| Brave Search MCP | Search | Internet search via Brave API | ⭐⭐⭐⭐ | ⭐⭐⭐⭐ |
| PostgreSQL MCP | Databases | Queries to PostgreSQL databases | ⭐⭐⭐ | ⭐⭐⭐⭐ |
| Cloudflare MCP | Cloud infrastructure | Cloudflare service management | ⭐⭐⭐ | ⭐⭐⭐ |
| Raygun MCP | Error monitoring | Tracking errors and performance | ⭐⭐⭐ | ⭐⭐⭐ |
| Vector Search MCP | Semantic search | Search by vector embeddings | ⭐⭐⭐ | ⭐⭐⭐ |
| Docker MCP | Containerization | Docker container management | ⭐⭐⭐ | ⭐⭐⭐⭐ |
Recommendations for Choosing a Platform
For Developers and Technical Experts
-
Developing Your Own MCP Server:
- If you are developing in TypeScript/JavaScript: choose FastMCP for a full set of features or EasyMCP for maximum simplicity
- For Python developers: FastAPI-MCP is an ideal choice for integration with existing APIs
- For high-load applications: Foxy Contexts on Go will provide maximum performance
-
Finding and Installing Existing Servers:
- For a general overview of the ecosystem: Portkey.ai, mcp.so, or Glama.ai
- For installation via the command line: mcp-get.com or mcpm.sh
- For developers who prefer a graphical interface: MCPHub
- For intelligent tool search: Smithery.ai
-
Hosting and Management:
- For simple managed hosting: Composio or MCPServer.cloud
- For integration with existing Cloudflare infrastructure: Cloudflare for MCP
- For centralized management of multiple servers: mcp.run
- For integration with automation and workflows: Pipedream MCP
-
Servers with Enhanced Security:
- For enterprise scenarios: Composio with authentication
- For automating workflows with secure access: Pipedream MCP
- For local security control: mcp-guardian
For Enterprises and Organizations
-
Small Teams and Startups:
- Use ready-made MCP servers from catalogs and frameworks for rapid development
- FastMCP or MCP-Framework will provide a balance between simplicity and functionality
- MCPHub will allow you to quickly start using existing servers
-
Medium and Large Organizations:
- Consider hosting platforms for centralized management: Composio or mcp.run
- For enterprise scenarios with high security requirements: mcp-guardian or Pipedream MCP
- Frameworks in Java (Quarkus MCP) or Go (Foxy Contexts) for high-load systems
-
Corporate Requirements:
- For integration with existing infrastructure: choose frameworks compatible with your stack
- For security and access control: hosting platforms with authentication
- For scaling: solutions in Go or Java with containerization support
Trends in the Development of MCP Platforms
Analyzing the current MCP ecosystem, several key trends can be identified:
-
Server Specialization - the emergence of increasingly specialized MCP servers for specific areas, such as finance, medicine, law, etc.
-
Security Improvement - increased attention to security, the emergence of additional authentication and authorization mechanisms for MCP servers.
-
Integration with Cloud Platforms - major cloud providers are integrating MCP into their platforms, simplifying deployment and management.
-
Tools for Non-Technical Users - the emergence of solutions that allow business users to create and manage MCP servers without deep technical knowledge.
-
Optimization for Mobile Devices - development of MCP servers taking into account the limitations of mobile devices and optimization for operation on low-performance equipment.
Frequently Asked Questions About MCP Platforms
What is MCP and why is it needed?
MCP (Model Context Protocol) is an open protocol that standardizes interaction between AI models and external tools/data. It allows AI assistants, such as Claude, to securely connect to external data sources and tools, expanding their capabilities.
Which MCP platform is best for beginners?
For beginners, it is recommended to use EasyMCP (TypeScript) or FastAPI-MCP (Python) if you are familiar with the respective languages. You can also use graphical tools such as MCPHub to manage existing servers without programming.
Can MCP be used with models other than Claude?
Yes, although the MCP protocol was originally introduced by Anthropic for Claude, it is open and can be used with other LLMs. Many clients, such as Cline and Cursor, already support MCP, and the list of compatible models continues to grow.
Is it safe to use MCP servers?
MCP servers can have different levels of security. Official servers usually follow recommended security practices, but caution should be exercised when using third-party servers. It is recommended to check the source code, use trusted sources, and limit server access to only the necessary resources.
What alternatives exist for MCP?
Alternatives to MCP include other frameworks for creating tools for AI, such as LangChain, LlamaIndex, API integrations without a standardized protocol, and proprietary solutions from different LLM providers. However, MCP is distinguished by standardization and ease of integration.
How to ensure security when using MCP servers?
To ensure security when using MCP servers, it is recommended to:
- Use servers with authentication support (Composio, Pipedream MCP)
- Limit server access to only the necessary resources
- Use control tools such as mcp-guardian
- Regularly update servers to the latest versions
- Conduct security audits for critical servers
Resources for Learning MCP
For in-depth study of MCP and work with platforms, we recommend the following resources:
-
Official Documentation:
-
Repositories on GitHub:
- modelcontextprotocol/servers - Reference implementations of MCP servers
- punkpeye/awesome-mcp-servers - Curated list of MCP servers
-
Communities:
- Discord server MCP - Active community of MCP developers
- Reddit r/mcp - Discussions and news on MCP
-
Training Materials:
-
Tools:
Concluding Recommendations
When choosing and using MCP platforms, it is recommended to:
-
Start Small - select a few basic MCP servers that meet your needs and gradually add new ones.
-
Study Examples - consider open-source examples of platform usage to understand best practices and potential pitfalls.
-
Participate in the Community - join discussions, ask questions, and share experiences with other MCP developers.
-
Follow Updates - the MCP protocol is actively evolving, so it is important to stay up to date with the latest changes and improvements.
-
Test Security - regularly check the security of your MCP integrations, especially when working with sensitive data.
-
Document Your Implementations - create documentation for your MCP servers and integrations to facilitate support and knowledge sharing within the team.
MCP opens new horizons for integrating AI into various systems and workflows. With the right platforms and tools, you can maximize the potential of this technology to solve your problems.
Radar Charts for Comparing MCP Platforms
Heatmap comparing the characteristics of various MCP platforms
https://claude.site/artifacts/9506227e-7e75-48b2-8620-4999fe9282be