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@Runapi.Ai/Happyhorse

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Enables creating and managing HappyHorse video generation tasks (edit, image-to-video, text-to-video) via RunAPI, with optional polling for completion and prici

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About

Enables creating and managing HappyHorse video generation tasks (edit, image-to-video, text-to-video) via RunAPI, with optional polling for completion and pricing lookup.

README

RunAPI HappyHorse MCP Server

HappyHorse API access for AI agents: create video generation tasks, poll results, and check pricing through one focused MCP server.

Works with Claude Code, Codex, Cursor, Windsurf, VS Code, Roo Code, and any MCP-compatible host.

npm version GitHub repository Apache-2.0 license MCP Server 4 models

Install | Tools | Models | Agent Prompts | Configuration | Links


Why This Package?

@runapi.ai/happyhorse-mcp is a focused Model Context Protocol server for the HappyHorse model line on RunAPI. It gives MCP-compatible assistants direct access to 3 endpoints and 4 model variants without loading the full RunAPI catalog.

Use this per-model server when an agent should stay scoped to HappyHorse. Use @runapi.ai/mcp when one assistant should discover every RunAPI model line.


Install

Add it to Claude Code:

claude mcp add happyhorse -s user -- npx -y @runapi.ai/happyhorse-mcp

Use project scope when the server should be shared with a repository:

claude mcp add happyhorse -s project -- npx -y @runapi.ai/happyhorse-mcp

Codex, Cursor, Windsurf, VS Code, Roo Code, and other MCP hosts can use the same stdio command:

{
  "mcpServers": {
    "happyhorse": {
      "command": "npx",
      "args": ["-y", "@runapi.ai/happyhorse-mcp"]
    }
  }
}

check_pricing works before sign-in. For task creation and status polling, ask your assistant to call the login tool. It opens a browser login and saves credentials to ~/.config/runapi/config.json, the same file used by runapi login. Headless and CI hosts can still set RUNAPI_API_KEY before starting the MCP host.

Ready-made examples are in examples/ for Claude, Cursor, Windsurf, VS Code, and Roo Code.


Tools

Tool Auth Purpose
edit_video Yes Create a HappyHorse edit video task and optionally wait for a terminal status. Returns the task id, status, output URLs, and pricing snapshot.
image_to_video Yes Create a HappyHorse image to video task and optionally wait for a terminal status. Returns the task id, status, output URLs, and pricing snapshot.
text_to_video Yes Create a HappyHorse text to video task and optionally wait for a terminal status. Returns the task id, status, output URLs, and pricing snapshot.
get_task Yes Fetch the current status and latest payload for an existing task.
check_pricing No Look up the current pricing snapshot for a HappyHorse model and endpoint.

Models

HappyHorse covers 4 model variants across 3 endpoints. Each tool accepts the models listed for it:

Tool Models
edit_video happyhorse-edit-video
image_to_video happyhorse-image-to-video
text_to_video happyhorse-character, happyhorse-text-to-video

Model availability can change between releases. Use check_pricing or the HappyHorse model page for the current catalog view.


Agent Prompts

Ask your assistant in natural language; it can inspect pricing, create the task, and return the task id plus output URLs.

Create a task

Run a HappyHorse edit video task with RunAPI.

The assistant can call check_pricing, then edit_video, and return the task id, status, and output URLs.

Submit without waiting

Create the task but don't wait for it to finish.

The assistant calls the create tool with wait: false and returns the task id. Check on it later with get_task.

Check pricing before creating

Check current HappyHorse pricing, then create the task if it matches my request.

The assistant calls check_pricing and can link to the HappyHorse model page for the canonical catalog entry.


Configuration

The server resolves auth in this order:

  1. RUNAPI_API_KEY environment variable, useful for headless and CI hosts
  2. ~/.config/runapi/config.json, created by the MCP login tool or runapi login
  3. No key, which still allows check_pricing

The config file is normally managed by login. A pre-provisioned headless config can use:

{
  "apiKey": "your_runapi_key"
}

Do not commit real API keys.


Links

Resource URL
HappyHorse model page https://runapi.ai/models/happyhorse
npm package @runapi.ai/happyhorse-mcp
GitHub repository runapi-ai/happyhorse-mcp
RunAPI MCP overview runapi.ai/mcp
RunAPI docs runapi.ai/docs

License

Licensed under the Apache License, Version 2.0.

from github.com/runapi-ai/happyhorse-mcp

Install @Runapi.Ai/Happyhorse in Claude Desktop, Claude Code & Cursor

Recommended · one command, every IDE
unyly install runapi-ai-happyhorse-mcp

Installs into Claude Desktop, Claude Code, Cursor & VS Code — handles npx, uvx and build-from-source repos for you.

First time? Get the CLI: curl -fsSL https://unyly.org/install | sh

Or configure manually

Run in your terminal:

claude mcp add runapi-ai-happyhorse-mcp -- npx -y @runapi.ai/happyhorse-mcp

FAQ

Is @Runapi.Ai/Happyhorse MCP free?

Yes, @Runapi.Ai/Happyhorse MCP is free — one-click install via Unyly at no cost.

Does @Runapi.Ai/Happyhorse need an API key?

No, @Runapi.Ai/Happyhorse runs without API keys or environment variables.

Is @Runapi.Ai/Happyhorse hosted or self-hosted?

A hosted option is available: Unyly runs the server in the cloud, no local setup required.

How do I install @Runapi.Ai/Happyhorse in Claude Desktop, Claude Code or Cursor?

Open @Runapi.Ai/Happyhorse on unyly.org, pick your client tab (Claude Desktop, Claude Code, Cursor) and press Install — the config is generated automatically, no JSON editing.

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