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io.github.AceDataCloud/mcp-happyhorse

Generate and edit Happy Horse AI videos through Ace Data Cloud

Cloud ProvidersPythonv2026.10.4.1

Happy Horse MCP Server

PyPI Python License

Model Context Protocol server for Happy Horse AI video generation and editing through the Ace Data Cloud API.

Capabilities

  • Text-to-video generation
  • First-frame image-to-video animation
  • Reference-to-video generation with 1-9 subject or style images
  • Video editing with up to 5 reference images
  • 720P and 1080P output
  • Single and batch task polling
  • Local stdio and hosted Streamable HTTP/SSE transports
  • Direct Bearer token and AceDataCloud OAuth authentication

Install

pip install mcp-happyhorse
export ACEDATACLOUD_API_TOKEN="your-token"
mcp-happyhorse

Get a token from platform.acedata.cloud.

Configure

Claude Desktop

{
  "mcpServers": {
    "happyhorse": {
      "command": "uvx",
      "args": ["mcp-happyhorse"],
      "env": {
        "ACEDATACLOUD_API_TOKEN": "your-token"
      }
    }
  }
}

Hosted MCP

{
  "mcpServers": {
    "happyhorse": {
      "url": "https://happyhorse.mcp.acedata.cloud/mcp",
      "headers": {
        "Authorization": "Bearer your-token"
      }
    }
  }
}

The hosted endpoint also supports OAuth-capable MCP clients.

Tools

ToolPurpose
happyhorse_generate_videoGenerate a video from text
happyhorse_generate_video_from_imageAnimate one first-frame image
happyhorse_generate_video_from_referencesGenerate from 1-9 reference images
happyhorse_edit_videoEdit a source video with up to 5 references
happyhorse_get_taskQuery one task
happyhorse_get_tasks_batchQuery multiple tasks
happyhorse_list_modelsList valid models for each action

Generation tools submit asynchronously when no callback_url is supplied. Keep the returned task_id, wait about 15 seconds, then call happyhorse_get_task until the response contains a final video_url or terminal error.

Models

ActionModelsDefault
Text-to-videohappyhorse-1.0-t2v, happyhorse-1.1-t2vhappyhorse-1.1-t2v
Image-to-videohappyhorse-1.0-i2v, happyhorse-1.1-i2vhappyhorse-1.1-i2v
Reference-to-videohappyhorse-1.0-r2v, happyhorse-1.1-r2vhappyhorse-1.1-r2v
Video edithappyhorse-1.0-video-edithappyhorse-1.0-video-edit

Generation duration is 3-15 seconds. Supported resolutions are 720P and 1080P. Text and reference generation support 16:9, 9:16, 1:1, 4:3, and 3:4. Image-to-video follows the input image ratio. Video-edit duration follows the source video.

Example Requests

Ask your MCP client:

Generate a 720P, 9:16 video of a white horse crossing a snowy ridge at sunrise.

Animate https://example.com/horse.jpg with a slow camera push and wind moving the mane.

Edit https://example.com/source.mp4 to preserve the camera motion but apply the costume style from https://example.com/reference.jpg. Keep the original audio.

Environment

VariableDefaultPurpose
ACEDATACLOUD_API_TOKENnoneAPI token for local stdio mode
ACEDATACLOUD_API_BASE_URLhttps://api.acedata.cloudAPI origin
HAPPYHORSE_REQUEST_TIMEOUT60HTTP request timeout in seconds
MCP_TRANSPORTstdiostdio or http
MCP_SERVER_URLnonePublic URL that enables hosted OAuth
LOG_LEVELINFOLogging level

Development

pip install -e ".[all]"
pytest --cov=core --cov=tools
ruff check .
mypy core tools main.py

Documentation

Documentation

License

MIT

Installation

Source-derived launch command. Check the maintainer’s required arguments and credentials before running:

bash
uvx mcp-happyhorse

Set up in your AI client

Merge this template into ~/Library/Application Support/Claude/claude_desktop_config.json. Keep existing servers. Add any arguments, credentials, and permissions required by the maintainer; this template has not been install-tested.

json
{
  "mcpServers": {
    "io-github-acedatacloud-mcp-happyhorse": {
      "command": "uvx",
      "args": [
        "mcp-happyhorse"
      ]
    }
  }
}

Restart Claude Desktop completely for changes to take effect. Confirm the server appears connected in the client’s tool list, then try a read-only example from its documentation.

Claude Desktop setup reference

Package

mcp-happyhorsepypi

Compatible MCP Clients

io.github.AceDataCloud/mcp-happyhorse works with any MCP-compatible client. Copy the config snippet from the Configuration section above and add it to the file shown for your client, then restart the application.

  • Claude Desktop~/Library/Application Support/Claude/claude_desktop_config.jsonRestart Claude Desktop completely for changes to take effect.
  • Cursor~/.cursor/mcp.jsonRestart Cursor for changes to take effect.
  • VS Code.vscode/mcp.jsonReload VS Code window for changes to take effect.
  • Windsurf~/.codeium/windsurf/mcp_config.jsonRestart Windsurf for changes to take effect.
  • Claude Code.mcp.jsonSave at the project root, then start Claude Code in that project and review the MCP server approval prompt. Keep real credentials out of shared files.

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