# motion-graphics

> Generate animated motion graphics videos from a text prompt using AI-generated React/Remotion code rendered on Modal.

## Overview

- **Endpoint**: `POST https://api.muapi.ai/api/v1/motion-graphics`
- **Model ID**: `motion-graphics`
- **Category**: text to video
- **Variant**: Motion Graphics
- **Family**: motion-graphics
- **Cost**: 0.63 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/motion-graphics
Content-Type: application/json
x-api-key: YOUR_API_KEY
```

**Minimum (required only):**

```json
{
  "prompt": "<prompt>"
}
```

**Full example (all params):**

```json
{
  "prompt": "<prompt>",
  "category": "auto",
  "images_list": "https://cdn.muapi.ai/uploads/photo1.jpg",
  "video_files": "https://cdn.muapi.ai/uploads/clip.mp4",
  "aspect_ratio": "16:9",
  "duration_seconds": 6
}
```

**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/motion-graphics \
  -H "x-api-key: $MUAPI_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"prompt":"<prompt>"}' | 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}/motion-graphics", headers=headers, json={"prompt":"<prompt>"})
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`, _required_):
  Describe the motion graphics animation to generate.

- **`category`** (`string`, _optional_):
  Animation category. Use 'auto' to let AI detect the best style, or pick a category for optimised results. Use 'slideshow', 'showcase', or 'reel' when providing images/videos.
  - Default: `"auto"`
  - Options: `"auto"`, `"infographics"`, `"text-animation"`, `"social-media"`, `"presentation"`, `"logo"`, `"product"`, `"3d"`, `"slideshow"`, `"showcase"`, `"reel"`

- **`images_list`** (`array`, _optional_):
  Optional images to incorporate into the animation (up to 6). Required for slideshow, showcase, and reel categories.

- **`video_files`** (`array`, _optional_):
  Optional video clips to use as background or showcase footage (up to 2).

- **`aspect_ratio`** (`string`, _optional_):
  Output canvas aspect ratio.
  - Default: `"16:9"`
  - Options: `"16:9"`, `"9:16"`, `"1:1"`

- **`duration_seconds`** (`int`, _optional_):
  Length of the animation in seconds (5–30).
  - Default: `6`

## 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 `motion-graphics`. See `muapi --help` for category-specific shortcuts (`muapi image generate`, `muapi video from-image`, etc.).

## Related Models
- [Motion Graphics](https://muapi.ai/playground/motion-graphics)
- [Motion Graphics Edit](https://muapi.ai/playground/motion-graphics-edit)

## Resources
- [Playground Page](https://muapi.ai/playground/motion-graphics)
- [API Reference](https://muapi.ai/playground/motion-graphics?tab=2)
- [Global llms.txt](https://muapi.ai/llms.txt)