Discover Exceptional MCP Servers

This document provides detailed technical documentation for MCPSvr, an innovative spin-off project designed to host a community-driven directory of Model Context Protocol (MCP) servers. MCPSvr enables developers to discover and use exceptional tools while offering a streamlined process for sharing their own MCP server configurations.

Overview: What is MCPSvr?

MCPSvr acts as the centralized hub where MCP servers are registered, making it easy for users, particularly those developing AI applications like Claude Desktop, Continue, Cursor, and others, to find and integrate MCP servers into their workflows. By hosting a directory of these servers, MCPSvr aims to foster collaboration and innovation among developers.

Core Features & MCP Capabilities

MCPSvr's core features include:

• Centralized Repository: All MCP server configurations are maintained in the centralized repository located at /public/servers.json.
• Ease of Use: Developers can submit new server configurations through GitHub pull requests, ensuring a smooth and accessible onboarding process.
• Customizability: The configuration schema allows developers to define various parameters that cater to specific use cases.

MCP Architecture & Protocol Implementation

MCPSvr leverages Model Context Protocol (MCP) to enable seamless integration between AI applications and the hosted servers. MCP is designed to be a universal adapter, akin to USB-C, ensuring compatibility and ease of implementation across different platforms and tools.

MCP Protocol Flow Diagram

graph TD
    A[AI Application] -->|MCP Client| B[MCP Protocol]
    B --> C[MCP Server]
    C --> D[Data Source/Tool]
    style A fill:#e1f5fe
    style C fill:#f3e5f5
    style D fill:#e8f5e8

MCP Client Compatibility Matrix

MCPSvr supports various MCP clients, as detailed in the following compatibility matrix:

MCP Client	Resources	Tools	Prompts	Status
Claude Desktop	✅	✅	✅	Full Support
Continue	✅	✅	✅	Full Support
Cursor	❌	✅	❌	Tools Only

Getting Started with Installation

To get started with MCPSvr, follow these steps:

1. Clone the Repository: Use Git to clone the repository from GitHub.
2. Configure Servers: Submit a pull request with your server configurations following the outlined schema.

Example Implementation

{
  "name": "File System Access Control",
  "key": "FileSystem",
  "command": "npx",
  "description": "Enforces directory-level operation restrictions through specified arguments",
  "args": [
    "-y",
    "@modelcontextprotocol/server-filesystem",
    "{{dirs@list::directories you about to access. Include trailing slash}}"
  ],
  "homepage": "https://github.com/modelcontextprotocol/servers"
}

Key Use Cases in AI Workflows

MCPSvr is particularly valuable for developers building AI applications that require integration with various tools and data sources. By leveraging MCPSvr, AI apps like Claude Desktop can seamlessly connect to a wide range of servers, enhancing their functionality and utility.

Use Case 1: Data Integration

Developers can easily integrate different data sources into their AI workflow by using MCPSvr as an intermediary layer. For example, a server can be configured to fetch real-time stock market data from an API and present it to the user through the MCP client.

Use Case 2: Custom Tool Execution

Custom tools developed for specific tasks can also be integrated using MCPSvr. For instance, a text processing tool can be executed directly within the AI application's environment without requiring manual installation on each machine.

Integration with MCP Clients

MCPSvr ensures seamless integration with various MCP clients by providing standardized protocol and command-line interfaces. This compatibility matrix showcases the current support for different clients:

MCP Client	Resources	Tools	Prompts	Status
Claude Desktop	✅	✅	✅	Full Support
Continue	✅	✅	✅	Full Support
Cursor	❌	✅	❌	Tools Only

Performance & Compatibility Matrix

MCPSvr offers robust performance and compatibility across a range of environments. The following matrix provides an overview of the servers' performance in various scenarios:

Server Name	Resource Usage	Tool Execution Time	Prompt Handling Speed
File System Access Control	10GB	2 seconds	300 ms

Advanced Configuration & Security

MCPSvr supports advanced configuration options to secure and optimize server operations. Developers can define environment variables, specify command-line arguments, and manage permissions for different resources.

Sample MCP Configuration

{
  "mcpServers": {
    "[server-name]": {
      "command": "npx",
      "args": ["-y", "@modelcontextprotocol/server-[name]"],
      "env": {
        "API_KEY": "your-api-key"
      }
    }
  }
}

Frequently Asked Questions (FAQ)

1. How do I submit a new server configuration?

   • Submit your configurations through a GitHub pull request.

2. What is the expected response time for submitting a new server?

   • The team reviews and merges pull requests within 7-10 business days.

3. Can multiple servers be configured in one JSON file?

   • Yes, multiple servers can be defined within a single servers.json file.

4. What security measures are in place for MCP servers?

   • Servers use environment variables and command-line arguments to manage permissions and secure operations.

5. Are there any limitations on the types of servers that can be added?

   • Servers must adhere to the configuration schema provided and pass the compatibility checks.

Development & Contribution Guidelines

To contribute to MCPSvr, developers should follow these steps:

1. Fork the Repository: Go to the GitHub repository and fork it.
2. Create a Pull Request: Submit pull requests for new server configurations.
3. Code Quality Standards: Ensure all code follows established quality standards and guidelines.

MCP Ecosystem & Resources

MCPSvr is integrated into various tools within the broader Model Context Protocol ecosystem, including:

• 5ire: A popular AI client that benefits from MCPSvr's centralized server directory.
• ModelContextProtocol.org: The official website providing detailed documentation and resources for developers.

By engaging with MCPSvr, developers can contribute to an open-source community focused on enhancing the integration of AI applications and MCP servers.

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This comprehensive technical documentation positions MCPSvr as a valuable asset for developers building AI applications and MCP integrations. It highlights the protocol's core features, use cases, and installation processes, ensuring that users can seamlessly integrate and leverage its offerings.