# flux-kontext-effects

> Flux Kontext Effects is a creative image and video model that applies stylized transformations, cinematic filters, and artistic reinterpretations to your inputs. Instead of generating new content from scratch, it enhances or reimagines existing images and videos with unique looks — ranging from surreal effects to realistic cinematic moods.

## Overview

- **Endpoint**: `POST https://api.muapi.ai/api/v1/flux-kontext-effects`
- **Model ID**: `flux-kontext-effects`
- **Category**: image to image
- **Variant**: Image Effects
- **Family**: kontext
- **Cost**: 0.04 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/flux-kontext-effects
Content-Type: application/json
x-api-key: YOUR_API_KEY
```

**Minimum (required only):**

```json
{
  "prompt": "<prompt>",
  "image_url": "https://example.com/your-image_url"
}
```

**Full example (all params):**

```json
{
  "prompt": "<prompt>",
  "image_url": "https://example.com/your-image_url",
  "name": "Age Progression"
}
```

**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/flux-kontext-effects \
  -H "x-api-key: $MUAPI_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"prompt":"<prompt>","image_url":"https://example.com/your-image_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}/flux-kontext-effects", headers=headers, json={"prompt":"<prompt>","image_url":"https://example.com/your-image_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`, _required_):
  Text prompt describing the image.

- **`image_url`** (`string`, _required_):
  URL of the input image.

- **`name`** (`string`, _optional_):
  The type of effect to apply to the image.
  - Default: `"Age Progression"`
  - Options: `"Age Progression"`, `"Background Change"`, `"Cartoonify"`, `"Color Correction"`, `"Expression Change"`, `"Face Enhancement"`, `"Hair Change"`, `"Object Removal"`, `"Professional Photo"`, `"Scene Composition"`, `"Style Transfer"`, `"Time of Day"`, `"Weather Effect"`

## 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 `flux-kontext-effects`. See `muapi --help` for category-specific shortcuts (`muapi image generate`, `muapi video from-image`, etc.).

## Related Models
- [Kontext Dev I2I](https://muapi.ai/playground/flux-kontext-dev-i2i)
- [Kontext Pro T2I](https://muapi.ai/playground/flux-kontext-pro-t2i)
- [Kontext Pro I2I](https://muapi.ai/playground/flux-kontext-pro-i2i)
- [Kontext Max T2I](https://muapi.ai/playground/flux-kontext-max-t2i)
- [Kontext Max I2I](https://muapi.ai/playground/flux-kontext-max-i2i)
- [Image Effects](https://muapi.ai/playground/flux-kontext-effects)
- [Kontext Dev T2I](https://muapi.ai/playground/flux-kontext-dev-t2i)

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