Happyhorse By Acedatacloud

HappyHorse by Ace Data Cloud

Generate or edit HappyHorse (Happy Horse) videos through Ace Data Cloud, including first-frame and reference-guided video; poll the same task for its result. This is an Ace Data Cloud integration, not an official HappyHorse or Amp plugin endorsement.

Setup and tool scope

Requires Amp native Skill MCP support, an existing Amp login, and ACEDATACLOUD_API_TOKEN in the environment that starts Amp.

Read README.md for installation, illustrated API-key setup, and troubleshooting. The sibling mcp.json connects only happyhorse-ace at https://happyhorse.mcp.acedata.cloud/mcp and limits tools to this service. Reuse an existing matching connection; do not add a second server or alter unrelated settings. Keep the API key in ACEDATACLOUD_API_TOKEN; never request it in the conversation, put it in a command argument, or print it. Load this Skill to expose its MCP tools. Use happyhorse_list_models once to inspect the supported choices; this is informational and does not prove API permissions or balance.

Generation and retrieval

1. Confirm the user wants this video operation and accepts its current pricing, parameters and output count. Choose a currently supported model and parameters with the user; do not silently substitute models, providers, prices, or resolution tiers.
2. Call happyhorse_generate_video exactly once for that requested operation. Use an edit tool only when the user provides authorized reference media and asks to edit it.
3. Save the returned task ID. Call happyhorse_get_task(task_id="<original task ID>") to retrieve the same task after pending results, disconnects or timeouts. Never submit generation again merely to poll.
4. Require an explicit terminal success (state=complete with success, or the returned finished timestamp and successful response). Failure is terminal too. A pending task or an early media URL is not completion. Do not invent IDs, output links, media availability, completion or billing. Report the final status and returned media links; preserve upstream errors (including rate limit and moderation meaning).
5. On an uncertain submission, inspect its original task/request before any new paid request. A failed result is not permission to retry, change the model, or use a fallback.

Amp reasoning can have its own usage charge. Installation/tool discovery and API metadata are distinct from inference, generation, terminal media, and the account's usage record.