MCP Server - Skyfire Integration MCP Server: Enabling Secure Payments in AI Applications

Overview: What is MCP Server - Skyfire Integration?

The mcp-server-skyfire project is an MCP server implementation that provides a standardized interface for integrating AI applications with the Skyfire payment system. This server allows AI models to leverage the Model Context Protocol (MCP) to facilitate secure and efficient payments, bridging the gap between advanced AI workflows and financial transactions. By adhering to a well-defined protocol and leveraging robust security features, mcp-server-skyfire ensures seamless integration with various MCP clients.

🔧 Core Features & MCP Capabilities

The core features of mcp-server-skyfire center around its ability to provide essential payment services through the Model Context Protocol. Key capabilities include:

• Tool Initialization: The server initializes a payment tool (make_payment) that allows AI applications to send payments securely.
• Parameter Validation: Ensures that incoming requests contain valid parameters, including the recipient's username and the payment amount.
• Error Handling: Implements comprehensive error handling for different scenarios, returning appropriate responses based on the nature of the failure.
• Security: Uses a Skyfire API key for secure authentication and authorization.

Parameter Implementation Details

The make_payment tool accepts two parameters:

• receiverUsername: A string representing the username of the recipient.
• amount: A string specifying the payment amount.

Example Response:

{
  "content": [
    {
      "type": "text",
      "text": "Payment of [amount] successfully sent to [username]"
    }
  ]
}

AI Application Compatibility

mcp-server-skyfire is designed to be compatible with various MCP clients, ensuring that a wide range of AI applications can leverage its payment functionality. The compatibility matrix below highlights the current support levels:

MCP Client	Resources	Tools	Prompts
Claude Desktop	✅	✅	✅
Continue	✅	✅	✅
Cursor	❌	✅	❌

⚙️ MCP Architecture & Protocol Implementation

The server architecture is built around the Model Context Protocol, which standardizes interactions between AI applications and the payment system. The implementation details include:

1. MCP Client Initialization: MCP clients connect to the mcp-server-skyfire via a custom command that installs the necessary dependencies.
2. Payment Tool Execution: Upon receiving an HTTP request, the server executes the payment tool (make_payment) with the provided parameters.

Mermaid Diagram: MCP Protocol Flow

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

Mermaid Diagram: Data Architecture

graph TD
    A[Client] --> B[API Key]
    B --> C[MCP Server]
    C -->|Payment Request| D[Database]
    D --> E[Transaction Log]
    style A fill:#f3e5f5
    style C fill:#e8f5e8
    style D fill:#d0f7d2

🚀 Getting Started with Installation

To deploy and run the mcp-server-skyfire, follow these steps:

1. Clone the Repository:

   git clone <repository-url>
   cd mcp-server-skyfire
   

2. Install Dependencies:

   npm install
   

3. Create Configuration File: Create a .env file in the root directory and add your Skyfire API key.

   SKYFIRE_API_KEY=your_api_key_here
   

4. Build the Project:

   npm run build
   

5. Run the Server:

   ./build/index.js
   

Or, via npm:

mcp-server-skyfire

💡 Key Use Cases in AI Workflows

Workflow Example 1: Expense Reporting Automation

In this scenario, an AI application (e.g., Continue) uses the make_payment tool to automate expense reporting and reconciliation. The server processes payment requests from various users and logs transactions for auditing purposes.

Technical Implementation:

async function handlePaymentRequest(request: PayRequest): Promise<PaymentResponse> {
  const { receiverUsername, amount } = request;
  // Validate and process payment
  if (isValidPayment) {
    return {
      content: [
        {
          type: "text",
          text: `Payment of ${amount} successfully sent to ${receiverUsername}`
        }
      ]
    };
  } else {
    throw new Error("Invalid Payment Request");
  }
}

Workflow Example 2: Freelancer Marketplace Integration

In a freelance marketplace, AI applications (like Cursor) can facilitate payments between freelancers and clients. The server ensures that all payment transactions are secure and logged appropriately.

Technical Implementation:

async function handlePaymentRequest(request: PayRequest): Promise<PaymentResponse> {
  const { receiverUsername, amount } = request;
  // Validate and process payment
  if (isValidPayment) {
    return {
      content: [
        {
          type: "text",
          text: `Payment of ${amount} successfully sent to ${receiverUsername}`
        }
      ]
    };
  } else {
    throw new Error("Invalid Payment Request");
  }
}

🔌 Integration with MCP Clients

mcp-server-skyfire is designed to work seamlessly with various MCP clients, ensuring that AI applications can leverage its payment capabilities without additional configuration. This server supports a range of tools, including:

• Claude Desktop: Offers full compatibility and enhanced user experiences.
• Continue: Provides robust API integration.
• Cursor: Compatible but limited in certain functionalities.

📊 Performance & Compatibility Matrix

The performance and compatibility matrix provides an overview of the server's capabilities across different clients.

Feature	Claude Desktop	Continue	Cursor
Tool Initialization	✅	✅	❌
Parameter Execution	✅	✅	❌
Error Handling	✅	✅	❌

🛠️ Advanced Configuration & Security

To enhance security and performance, developers can configure the server using environment variables. The following sample configuration demonstrates setting up mcp-server-skyfire:

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

❓ Frequently Asked Questions (FAQ)

Q1: How do I integrate my AI application with mcp-server-skyfire?

To integrate your AI application, follow the provided setup instructions and ensure that it supports MCP clients.

Q2: What security measures are in place for payments processed by this server?

The server uses a Skyfire API key for secure authentication and authorization to prevent unauthorized access.

Q3: Can I customize the payment tool (make_payment) for my specific needs?

Yes, you can extend or modify the make_payment tool to accommodate your unique requirements.

Q4: How do I handle errors during the payment process?

The server implements comprehensive error handling, returning appropriate responses based on different failure scenarios.

Q5: Are there any limitations in using this server for certain AI applications?

Some AI applications may have limited compatibility due to specific feature support. Refer to the MCP client matrix for details.

👨‍💻 Development & Contribution Guidelines

Contributions are welcome! If you wish to contribute to mcp-server-skyfire, please follow these guidelines:

• Setup: Clone the repository and install dependencies.
• Coding Standards: Adhere to existing coding standards and practices.
• Testing: Write tests for new or modified features.

🌐 MCP Ecosystem & Resources

For more information on integrating your AI applications with mcp-server-skyfire, visit the Model Context Protocol documentation site. Join our community forum for discussions, tutorials, and support.

This comprehensive documentation provides a detailed overview of how to integrate mcp-server-skyfire into various AI workflows while ensuring robust security and performance.