# wan2.2-animate > Wan2.2 Animate is a video-to-video model for animating a character or replacing a character in existing video clips. It replicates holistic movement and facial expressions from a reference video or pose while preserving the target character’s appearance. You upload both an image (for the character) and a video containing motion/expression, and the model generates a video where the character in your image moves like the reference. Supports 480p or 720p, up to 120 seconds ## Overview - **Endpoint**: `POST https://api.muapi.ai/api/v1/wan2.2-animate` - **Model ID**: `wan2.2-animate` - **Category**: video to video - **Variant**: Anime Video - **Family**: wan2.2 - **Cost**: 0.35 credits per call (some models compute cost dynamically based on params) ## API Usage MuApi uses a **submit-then-poll** pattern: submit a job, get a `request_id`, then poll the predictions endpoint until `status` is `completed`. Optionally pass `?webhook=YOUR_URL` on the submit call to receive a POST callback when the job finishes (skip polling). **Authentication**: send your MuApi key in the `x-api-key` header. Get one at https://muapi.ai/access-keys. ### 1. Submit a job ```http POST https://api.muapi.ai/api/v1/wan2.2-animate Content-Type: application/json x-api-key: YOUR_API_KEY ``` **Minimum (required only):** ```json { "image_url": "https://example.com/your-image_url", "video_url": "https://example.com/your-video_url" } ``` **Full example (all params):** ```json { "prompt": "", "image_url": "https://example.com/your-image_url", "video_url": "https://example.com/your-video_url", "mode": "animate", "resolution": "480p" } ``` **Response:** ```json { "request_id": "abc123", "status": "processing" } ``` ### 2. Poll for the result ```http GET https://api.muapi.ai/api/v1/predictions/{request_id}/result x-api-key: YOUR_API_KEY ``` Possible `status` values: `queued`, `pending`, `processing`, `completed`, `failed`, `cancelled`. Poll every 2-5 seconds until terminal. When `completed`, the result URLs are in the `outputs` array. **Example response when `completed`:** ```json { "id": "abc123", "status": "completed", "outputs": [ "https://cdn.muapi.ai/.../output.png" ], "urls": { "get": "https://api.muapi.ai/api/v1/predictions/abc123/result" }, "created_at": "2026-05-08T12:34:56Z", "has_nsfw_contents": [] } ``` ### cURL ```bash # 1. Submit REQUEST_ID=$(curl -s -X POST https://api.muapi.ai/api/v1/wan2.2-animate \ -H "x-api-key: $MUAPI_API_KEY" \ -H "Content-Type: application/json" \ -d '{"image_url":"https://example.com/your-image_url","video_url":"https://example.com/your-video_url"}' | jq -r .request_id) # 2. Poll until completed while :; do RESP=$(curl -s https://api.muapi.ai/api/v1/predictions/$REQUEST_ID/result -H "x-api-key: $MUAPI_API_KEY") STATUS=$(echo "$RESP" | jq -r .status) [ "$STATUS" = "completed" ] && echo "$RESP" | jq .outputs && break [ "$STATUS" = "failed" ] && echo "$RESP" && exit 1 sleep 3 done ``` ### Python ```python import os, time, requests API = "https://api.muapi.ai/api/v1" headers = {"x-api-key": os.environ["MUAPI_API_KEY"]} r = requests.post(f"{API}/wan2.2-animate", headers=headers, json={"image_url":"https://example.com/your-image_url","video_url":"https://example.com/your-video_url"}) request_id = r.json()["request_id"] while True: res = requests.get(f"{API}/predictions/{request_id}/result", headers=headers).json() if res["status"] == "completed": print(res["outputs"]); break if res["status"] == "failed": raise RuntimeError(res.get("error")); time.sleep(3) ``` ## Input Schema The API accepts the following input parameters: - **`prompt`** (`string`, _optional_): Optional prompt for generating video. - **`image_url`** (`string`, _required_): URL of the input image. - **`video_url`** (`string`, _required_): URL of the input video. - **`mode`** (`string`, _optional_): Animate Mode: animate the character in input image with movements from the input video. Replace Mode: replace the character in input video with the character in input image. - Default: `"animate"` - Options: `"animate"`, `"replace"` - **`resolution`** (`string`, _optional_): The resolution of the generated video. - Default: `"480p"` - Options: `"480p"`, `"720p"` ## Output Schema The polling endpoint returns the following fields: - **`id`** (`string`): The request ID. - **`status`** (`string`): One of `queued`, `pending`, `processing`, `completed`, `failed`, `cancelled`. - **`outputs`** (`array`): URLs to generated images/videos/audio. Empty until `status` is `completed`. - **`urls.get`** (`string`): Self-link to re-fetch this prediction. - **`error`** (`string` | `null`): Error message if `status` is `failed`. - **`created_at`** (`string`): ISO-8601 timestamp of when the request was created. - **`has_nsfw_contents`** (`array of boolean`): Per-output NSFW detection flags. ## Webhooks (optional) Append `?webhook=https://your-server/path` to the submit URL. When the job reaches a terminal state, MuApi will POST the same shape as the polling response to your URL — no polling needed. ## Agent Integration MuApi ships an MCP server and CLI so agents (Claude Code, Cursor, custom) can call this endpoint without writing HTTP code: ```bash # Install the CLI npm install -g muapi-cli # Authenticate once muapi auth login # Expose all MuApi models as MCP tools to your agent muapi mcp serve ``` The MCP server exposes tools that wrap submit + poll for every model, including `wan2.2-animate`. See `muapi --help` for category-specific shortcuts (`muapi image generate`, `muapi video from-image`, etc.). ## Related Models - [Image to Video](https://muapi.ai/playground/wan2.2-image-to-video) - [Edit Video](https://muapi.ai/playground/wan2.2-edit-video) - [Text to Video](https://muapi.ai/playground/wan2.2-text-to-video) - [Anime Video](https://muapi.ai/playground/wan2.2-animate) - [Fast Text to Video](https://muapi.ai/playground/wan2.2-5b-fast-t2v) - [Audio to Video](https://muapi.ai/playground/wan2.2-speech-to-video) ## Resources - [Playground Page](https://muapi.ai/playground/wan2.2-animate) - [API Reference](https://muapi.ai/playground/wan2.2-animate?tab=2) - [Global llms.txt](https://muapi.ai/llms.txt)