# pinterest-publish > Publish a video or image Pin to a connected Pinterest board. ## Overview - **Endpoint**: `POST https://api.muapi.ai/api/v1/pinterest-publish` - **Model ID**: `pinterest-publish` - **Category**: other - **Variant**: Pinterest Publish - **Family**: social - **Cost**: 0.02 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/pinterest-publish Content-Type: application/json x-api-key: YOUR_API_KEY ``` **Minimum (required only):** ```json { "account_id": 0, "media_url": "https://example.com/your-media_url" } ``` **Full example (all params):** ```json { "account_id": 0, "media_url": "https://example.com/your-media_url", "caption": "", "title": "", "board_id": "", "link": "" } ``` **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/pinterest-publish \ -H "x-api-key: $MUAPI_API_KEY" \ -H "Content-Type: application/json" \ -d '{"account_id":0,"media_url":"https://example.com/your-media_url"}' | jq -r .request_id) # 2. Poll until completed while :; do RESP=$(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}/pinterest-publish", headers=headers, json={"account_id":0,"media_url":"https://example.com/your-media_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: - **`account_id`** (`integer`, _required_): ID of the connected Pinterest account. - **`media_url`** (`string`, _required_): Public URL of the video or image to pin. - **`caption`** (`string`, _optional_): Pin description. - Default: `""` - **`title`** (`string`, _optional_): Pin title. - Default: `""` - **`board_id`** (`string`, _optional_): Pinterest board ID to pin to. Leave blank for default board. - Default: `""` - **`link`** (`string`, _optional_): URL the pin links to. - Default: `""` ## 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 `pinterest-publish`. See `muapi --help` for category-specific shortcuts (`muapi image generate`, `muapi video from-image`, etc.). ## Related Models - [YouTube Publish](https://muapi.ai/playground/youtube-publish) - [Instagram Publish](https://muapi.ai/playground/instagram-publish) - [TikTok Publish](https://muapi.ai/playground/tiktok-publish) - [Facebook Publish](https://muapi.ai/playground/facebook-publish) - [LinkedIn Publish](https://muapi.ai/playground/linkedin-publish) - [Pinterest Publish](https://muapi.ai/playground/pinterest-publish) - [X Publish](https://muapi.ai/playground/x-publish) - [Threads Publish](https://muapi.ai/playground/threads-publish) - [YouTube Set Thumbnail](https://muapi.ai/playground/youtube-set-thumbnail) - [YouTube Update Metadata](https://muapi.ai/playground/youtube-update-metadata) ## Resources - [Playground Page](https://muapi.ai/playground/pinterest-publish) - [API Reference](https://muapi.ai/playground/pinterest-publish?tab=2) - [Global llms.txt](https://muapi.ai/llms.txt)