# Create Collection — Bannerbear

> Generates multiple Images based on a Template Set. See the docs here.

- Key: `bannerbear-create-collection`
- Type: Action (Write)
- Version: 0.0.2
- App: Bannerbear (`bannerbear`) — https://pipedream.com/apps/bannerbear.md
- This page (HTML): https://pipedream.com/apps/bannerbear/actions/create-collection
- Hints: destructive · open-world
- Source: https://github.com/PipedreamHQ/pipedream/blob/master/components/bannerbear/actions/create-collection/create-collection.mjs

## Description

Generates multiple Images based on a Template Set. [See the docs here](https://developers.bannerbear.com/#post-v2-collections).

## Props

| Prop | Type | Required | Description |
|---|---|---|---|
| `templateSet` | `string` | Yes | The template set UID that you want to use. Options are loaded from the connected account. |
| `modifications` | `string` | Yes | A list of modifications you want to make. See Create an image for more details on the child parameters. Unlike an Image the modifications list is not always required for a Video, for example: [{"name": "message", "text": "test message"}]. |
| `webhookUrl` | `string` | No | A url to POST the full Animated Gif object to upon rendering completed. |
| `metadata` | `string` | No | Any metadata that you need to store e.g. ID of a record in your DB. |
| `transparent` | `boolean` | No | Render the collection with a transparent background. Default is false. |

## Run it

**MCP**

```ts
import { Client } from "@modelcontextprotocol/sdk/client/index.js"
import { StreamableHTTPClientTransport } from "@modelcontextprotocol/sdk/client/streamableHttp.js"
import { PipedreamClient } from "@pipedream/sdk"

const pd = new PipedreamClient({
  projectId: process.env.PIPEDREAM_PROJECT_ID!,
  clientId: process.env.PIPEDREAM_CLIENT_ID!,
  clientSecret: process.env.PIPEDREAM_CLIENT_SECRET!,
  projectEnvironment: "production",
})

const accessToken = await pd.rawAccessToken

const transport = new StreamableHTTPClientTransport(
  new URL("https://remote.mcp.pipedream.net/v3"),
  {
    requestInit: {
      headers: {
        Authorization: `Bearer ${accessToken}`,
        "x-pd-project-id": process.env.PIPEDREAM_PROJECT_ID!,
        "x-pd-environment": "production",
        "x-pd-external-user-id": "{external_user_id}", // any stable ID for this user in your system
        "x-pd-app-slug": "bannerbear",
      },
    },
  },
)

const mcp = new Client({ name: "my-agent", version: "1.0.0" })
await mcp.connect(transport)

const { tools } = await mcp.listTools()

// listTools() hands your model this tool's input schema, so it can
// fill the arguments itself:
const result = await mcp.callTool({
  name: "bannerbear-create-collection",
  arguments: {
    templateSet: "Template Set UID",
    modifications: "Modifications",
  },
})
```

**TypeScript**

```ts
import { PipedreamClient } from "@pipedream/sdk"

const pd = new PipedreamClient({
  projectId: process.env.PIPEDREAM_PROJECT_ID!,
  clientId: process.env.PIPEDREAM_CLIENT_ID!,
  clientSecret: process.env.PIPEDREAM_CLIENT_SECRET!,
  projectEnvironment: "production",
})

const result = await pd.actions.run({
  id: "bannerbear-create-collection",
  externalUserId: "{external_user_id}", // any stable ID for this user in your system
  configuredProps: {
    bannerbear: { authProvisionId: "apn_xxxxxxx" },
    templateSet: "Template Set UID",
    modifications: "Modifications",
  },
})

console.log(result)
```

**cURL**

```bash
curl -X POST https://api.pipedream.com/v1/connect/{project_id}/actions/run \
  -H "Content-Type: application/json" \
  -H "X-PD-Environment: production" \
  -H "Authorization: Bearer {access_token}" \
  -d '{
    "external_user_id": "{external_user_id}",
    "id": "bannerbear-create-collection",
    "configured_props": {
      "bannerbear": { "authProvisionId": "apn_xxxxxxx" },
      "templateSet": "Template Set UID",
      "modifications": "Modifications"
    }
  }'
```

---

- App: https://pipedream.com/apps/bannerbear.md · All apps: https://pipedream.com/apps