piapi-mcp-server: Integrating Midjourney and Other AI Tools into Claude Desktop and Cursor

Overview: What is piapi-mcp-server?

piapi-mcp-server is a TypeScript-based Model Context Protocol (MCP) server that facilitates seamless integration of various AI tools and services with Claude Desktop, Continue, Cursor, among others. This server allows users to generate media content such as images, videos, music, lyrics, and more directly from Claude or any other MCP-compatible applications. By leveraging the Model Context Protocol, piapi-mcp-server enables a unified interface that simplifies interactions between AI applications and diverse data sources and tools.

🔧 Core Features & MCP Capabilities

Image Generation

• Flux: Generate images based on text or image prompts.
• Hunyuan Video: Produce videos from text/image prompts.
• Skyreels: Create videos using image prompts.
• Wan: Generate videos through text/image inputs.
• Midjourney Imagine and Other: Handle image generation tasks for Midjourney.

Audio & Music Generation

• MMAudio: Synthesize music from video content.
• TTS Zero-Shot Voicing: Create voice outputs from text commands.
• Suno Lyrics and Music: Generate lyrics along with corresponding songs.
• Udio Music and Lyrics: Produce both audio tracks and their accompanying words.
• Luma Dream Machine Video Generation: Create videos using advanced AI effects.

Advanced Generations

• Kling: Handle video generation and visual effects creation.
• Trellis 3D Model: Generate 3D models from image prompts.

Workflow Optimization

Integrating these functionalities within the MCP framework allows for more sophisticated workflow planning inside LLMs, enhancing both efficiency and creative output.

⚙️ MCP Architecture & Protocol Implementation

The piapi-mcp-server implements the protocol by defining endpoints that correspond to various AI services. These endpoints are designed to handle requests from the MCP clients (e.g., Claude Desktop or Cursor) and route them appropriately to the backend tools. This modular approach ensures that individual components can be updated independently without affecting the overall system.

🚀 Getting Started with Installation

Prerequisites

• Node.js 16.x or higher
• npm or yarn
• A PiAPI API key (available at piapi.ai)

Installation Steps

1. Clone the repository and navigate to the project folder:

   git clone https://github.com/apinetwork/piapi-mcp-server
   cd piapi-mcp-server
   

2. Install the necessary dependencies:

   npm install
   

3. Build the project for runtime execution:

   npm run build
   

After building, a dist/index.js file will be generated. This can then be configured to work with applications such as Claude Desktop and Cursor.

Optional Testing via MCP Inspector

For developers and users who wish to test the server's functionality before full deployment:

1. Create a .env file in the project root directory for environment variables, including your API key.

   PIAPI_API_KEY=your_api_key_here
   

2. Start the MCP Inspector with a custom timeout setting if needed (e.g., 60 seconds):

   npm run inspect
   

💡 Key Use Cases in AI Workflows

Real-World Scenario: Generating an Image of a Cat for Content Creation

1. AI Tool Selection: The user selects piapi-mcp-server as the tool via MCP protocol from their AI application.
2. User Input: The AI application passes a text prompt "a cute cat" to generate an image.
3. Server Processing: The server sends this request to Flux for image generation and returns the result.
4. Result Display: The generated image is displayed within the AI application interface, ready for immediate use.

Workflow Optimization for Video Production

Using piapi-mcp-server, a video production workflow could integrate multiple steps:

1. Generate video thumbnails using Hunyuan or Skyreels.
2. Insert voice-over using TTS Zero-Shot Voicing with appropriate scripts generated by Claude.
3. Fine-tune the content and layout changes needed for 3D models through Klimg.
4. Combine all elements to create a polished final product.

🔌 Integration with MCP Clients

The server enables seamless connection to major MCP clients:

• Claude Desktop: A configuration update in claude_desktop_config.json registers piapi-mcp-server as one of the available choices.
• Cursor: A similar setup involving adding a new entry in mcp_server_config allows Cursor users to utilize piapi's services.

📊 Performance & Compatibility Matrix

MCP Client Compatibility

MCP Client	Integration Status
Claude Desktop	✅ Full Support
Continue	✅ Full Support
Cursor	❌ Limited Tools Only

🛠️ Advanced Configuration & Security

Users can customize the server's behavior by adjusting environment variables and command-line arguments. Enhanced security configurations, such as SSL enforcement, are also possible.

Environment Variable Example

{
  "mcpServers": {
    "piapi": {
      "command": "node",
      "args": ["/absolute/path/to/piapi-mcp-server/dist/index.js"],
      "env": {
        "PIAPI_API_KEY": "your_api_key_here"
      }
    }
  }
}

❓ Frequently Asked Questions (FAQ)

Q1: How do I integrate piapi-mcp-server with Claude Desktop?

• A1: Configure your claude_desktop_config.json with the server's details.

Q2: Can this server be used for video generation tasks exclusively?

• A2: While primarily configured to handle multiple tasks, there are limitations based on timeout settings due to Claude’s constraints. Adjustments can help manage longer processes.

Q3: What tools does piapi-mcp-server support currently?

• A3: Supports various tools like Flux, Hunyuan, Skyreels, and others for diverse use cases.

Q4: How do I test piapi-mcp-server using MCP Inspector?

• A4: Run npm run inspect with appropriate timeout settings as documented.

Q5: What are the known limitations of this server?

• A5: Due to Claude’s timeout limitations, some heavy tasks like video and image generation might not complete in time. Testing with MCP Inspector can help mitigate these issues.

👨‍💻 Development & Contribution Guidelines

Contributions are welcomed! Developers interested in contributing or expanding functionality should follow the repository guidelines and submit pull requests for review.

🌐 MCP Ecosystem & Resources

For more information about Model Context Protocol (MCP) and related tools, visit modelcontextprotocol.io. The official documentation provides extensive details on implementation best practices and common use cases.

---

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

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

MCP Configuration Sample

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

This comprehensive documentation positions piapi-mcp-server as a crucial tool for integrating various AI services, enhancing the capabilities of applications like Claude Desktop and Cursor through Model Context Protocol.