Flyworks MCP Server

What does “Flyworks” MCP Server do?

The Flyworks MCP Server is a Model Context Protocol (MCP) server that provides a user-friendly interface to the Flyworks API, enabling rapid and free lipsync video creation for a variety of digital avatars, ranging from realistic to cartoon styles. By connecting AI assistants with the capabilities of the Flyworks platform, it allows developers and creative professionals to easily generate lipsynced videos using avatar footage and audio clips or even produce avatars directly from images or videos. The server supports both synchronous and asynchronous operations, streamlining workflows for applications in digital content creation, virtual humans, and interactive media experiences.

List of Prompts

No information about prompt templates is provided in the repository.

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List of Resources

No explicit MCP resources are listed in the documentation or repository.

List of Tools

No explicit list of tool definitions is provided in the repository or its documentation.

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Use Cases of this MCP Server

• Lipsync Video Generation: Instantly create lipsynced videos for digital avatars by providing an avatar video and an audio clip. This speeds up the animation process for virtual assistants, influencers, or digital characters.
• Text-to-Speech Animation: Input text to generate audio using TTS and synchronize it with avatar footage, making it easy to create multilingual or dynamic video content.
• Avatar Creation from Media: Generate new digital human avatars directly from images or videos, enabling rapid prototyping and diverse character generation for games or virtual worlds.
• Async and Sync Workflows: Choose between synchronous and asynchronous modes for different workflow needs, supporting integration in both real-time and batch processing pipelines.

How to set it up

Windsurf

No Windsurf-specific setup instructions are provided.

Claude

1. Ensure Python 3.8+ and dependencies (httpx, mcp[cli]) are installed.
2. Open Claude > Settings > Developer > Edit Config > claude_desktop_config.json.
3. Add the Flyworks MCP Server configuration as shown below.
4. Insert your API token and adjust paths as needed.
5. Save the file and restart Claude Desktop.
6. Verify the server is active and available.

Example JSON configuration:

{
  "mcpServers": {
    "flyworks": {
      "command": "uvx",
      "args": [
        "flyworks-mcp",
        "-y"
      ],
      "env": {
        "FLYWORKS_API_TOKEN": "your_api_token_here",
        "FLYWORKS_API_BASE_URL": "https://hfw-api.hifly.cc/api/v2/hifly",
        "FLYWORKS_MCP_BASE_PATH": "/path/to/your/output/directory"
      }
    }
  }
}

Note: Secure your API keys using environment variables as shown in the env section above.

Cursor

No Cursor-specific setup instructions are provided.

Cline

No Cline-specific setup instructions are provided.

How to use this MCP inside flows

Using MCP in FlowHunt

To integrate MCP servers into your FlowHunt workflow, start by adding the MCP component to your flow and connecting it to your AI agent:

Click on the MCP component to open the configuration panel. In the system MCP configuration section, insert your MCP server details using this JSON format:

{
  "flyworks": {
    "transport": "streamable_http",
    "url": "https://yourmcpserver.example/pathtothemcp/url"
  }
}

Once configured, the AI agent is now able to use this MCP as a tool with access to all its functions and capabilities. Remember to change “flyworks” to whatever the actual name of your MCP server is and replace the URL with your own MCP server URL.

Overview

Roots support: Not mentioned

Sampling support: Not mentioned

Between these two tables, Flyworks MCP provides a clear overview, license, and secure configuration, but lacks documentation on prompts, resources, and tools. As such, it is best suited for straightforward avatar lipsync workflows but may require further protocol-specific enhancements for MCP-compliant integrations.

Our opinion

Based on the above, we rate this MCP server a 4 out of 10 for general MCP protocol utility: strong in its focused use case, but lacking broader MCP features and documentation.

MCP Score