Remote MCP Server on Cloudflare (Without Auth)

Overview: What is Remote MCP Server?

This example showcases how to deploy a remote Model Context Protocol (MCP) server that does not require authentication on Cloudflare Workers. The server allows AI applications such as Claude Desktop, Continue, Cursor, and others to connect to specific data sources and tools through the Model Context Protocol with ease.

🔧 Core Features & MCP Capabilities

The core capabilities of this Remote MCP Server include:

• Deployment via one-click buttons or manual deployment using Cloudflare Workers.
• Customization to add your own tools.
• Access control for secrets and API keys.
• Compatibility with various AI applications through MCP clients.

Key Technical Details

1. Deployment Options:

   • One-click button: npm create cloudflare@latest -- my-mcp-server --template=cloudflare/ai/demos/remote-mcp-authless
   • Cloudflare Workers CLI:

     git clone <repository-url>
     cd <repository-directory>
     npm install
     npx wrangler login
     npx wrangler deploy
     

2. Securing Secrets:

   • Production secrets can be managed via Cloudflare’s secret management or Wrangler commands.
   • Local development secrets should be stored securely in .dev.vars files.

3. Customization: Add tools through the init() method of your custom implementation class.

Real-World AI Workflow Scenarios

Use Case 1: Financial Analysis Tool Integration

Imagine integrating a financial analysis tool that provides stock price predictions into an AI application like Claude Desktop. This integration can be achieved by setting up a Remote MCP Server with tools for fetching and analyzing stock data, which Claude can query directly.

Use Case 2: Medical Diagnosis Tool Deployment

Deploy a medical diagnosis tool on the Remote MCP Server to enable doctors or AI applications to gather patient symptoms, retrieve relevant diagnoses from a database, and suggest treatment options via MCP requests.

⚙️ MCP Architecture & Protocol Implementation

The architecture of this Remote MCP Server leverages Cloudflare Workers for hosting the server. The server interacts with clients using the Model Context Protocol (MCP) over SSE (Server-Sent Events).

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

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

🚀 Getting Started with Installation

One-Click Deployment

To quickly get started, use the one-click deploy button:

Alternatively, follow these manual steps:

1. Clone the Repository:

   git clone <repository-url>
   cd <repository-directory>
   

2. Install Dependencies:

   npm install
   

3. Login to Cloudflare:

   npx wrangler login
   

4. Deploy the Worker:

   npx wrangler deploy
   

💡 Key Use Cases in AI Workflows

Scenario 1: Financial Analysis Tool Integration

A financial analysis tool can provide valuable data to AI applications like Claude Desktop for making informed investment decisions.

Scenario 2: Medical Diagnosis Tool Deployment

Medical professionals and AI healthcare solutions can benefit from deploying a remote medical diagnosis tool, enhancing diagnostic accuracy with real-time patient data integration.

🔌 Integration with MCP Clients

Ensure compatibility between your Remote MCP Server and various MCP clients. The following steps outline how to connect the server:

1. Configure MCP Client:
   • Use Cloudflare AI Playground or local tools like Claude Desktop.
2. Enter URL:
   • For API access: <server-url>/sse
3. Connect Tools:
   • Access your custom tools from within the connected client.

📊 Performance & Compatibility Matrix

The performance and compatibility of this server are designed to ensure seamless integration with various MCP clients, focusing on real-time data exchanges and optimal resource utilization.

Example Configuration Code

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

🛠️ Advanced Configuration & Security

Managing Secrets

• Cloudflare Dashboard: Create and manage secrets via the Cloudflare dashboard.
• Wrangler Commands: Use npx wrangler secret put to securely store sensitive data.

Accessing Secrets in Code

// Example in src/index.ts
export default {
  async fetch(
    request: Request,
    env: Env,
    ctx: ExecutionContext
  ): Promise<Response> {
    const apiKey = env.YOUR_SECRET_NAME;
    // ... rest of your code
  },
};

❓ Frequently Asked Questions (FAQ)

1. Can I integrate this server with multiple MCP clients?

   • Yes, the server supports integration with various MCP clients including Claude Desktop, Continue, and Cursor.

2. How do I manage secrets securely?

   • Use Cloudflare's secret management or Wrangler commands for secure storage of sensitive data.

3. What are the performance implications of deploying this server?

   • The design ensures efficient real-time data exchanges with minimal latency.

4. Can I customize tools beyond what is provided in the examples?

   • Absolutely! Add your own tools and integrate them through the init() method in src/index.ts.

5. Is there a limit to the number of tools I can add?

   • The architecture supports a scalable addition of tools, ensuring flexibility for diverse use cases.

👨‍💻 Development & Contribution Guidelines

Contributions are welcome! Fork the repository and submit pull requests with your features or improvements. Ensure all code adheres to our coding standards and includes necessary tests.

🌐 MCP Ecosystem & Resources

Explore the broader MCP ecosystem, including resources for developers working on AI applications:

• GitHub Repository: cloudflare/ai
• MCP Documentation: Model Context Protocol Docs

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This comprehensive guide positions the Remote MCP Server as a robust tool for integrating various AI applications with custom data sources and tools. By leveraging Cloudflare Workers, developers can easily deploy and manage their servers while maintaining high performance and security standards.