> ## Documentation Index
> Fetch the complete documentation index at: https://docs.pollo.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Pollo MCP Server

> Pollo AI API's Model Context Protocol (MCP) server enables interaction with powerful Text/Image to video generation APIs. Learn more details here.

## Features

* Generate video from image or text prompt
* Get generation task status
* Automatically download the generated video

**Note**: Before using the service, you need to have the [Pollo AI API key](https://api.pollo.ai/api-keys).

## Installation

```bash theme={null}
npm install -g pollo-mcp
```

## Quick Start

Pollo MCP Server implements the [Model Context Protocol (MCP)](https://github.com/anthropics/model-context-protocol) specification and can be used as a server to interact with MCP-compatible clients (such as Cursor).

### Quickstart with Cursor

1. [Get your API key](https://api.pollo.ai/api-keys) from Pollo AI API platform.
2. Make sure that you already installed [Node.js and npm](https://docs.npmjs.com/downloading-and-installing-node-js-and-npm).

Go to `Cursor → Preferences → Cursor Settings → MCP Tools → New MCP Server`, add config.

```json theme={null}
{
  "mcpServers": {
    "pollo.ai": {
      "command": "npx",
      "args": ["-y", "mcp-server-pollo"],
      "env": {
        "POLLO_AI_BASE_URL": "https://pollo.ai",
        "POLLO_AI_API_KEY": "<your-api-key>",
        "POLLO_AI_HOME_DIR": "<path to save generated videos>",
        "POLLO_AI_VIDEO_MODEL_IMG": "<Model for generating videos from images, optional, pollo-v1-6 is used by default, multiple models are separated by commas>",
        "POLLO_AI_VIDEO_MODEL_TEXT": "<Model for generating videos from text, optional, pollo-v1-6 is used by default, multiple models are separated by commas>"
      }
    }
  }
}
```

That's it. Your MCP client can now interact with Pollo.ai through these tools.

### Tools

* **text2video**

  * Generate video from text prompt.
  * Input: `model`(object)，supports multiple models, for a detailed list, see [Pollo AI API Platform](/m/pollo/pollo-v1-6)
    * `modelBrand`(required, string), *e.g., pollo, kling-ai, runway.*
    * `modelAlias`(required, string), *e.g., pollo-v1-6, kling-v2, runway-gen-4-turbo.*
    * `prompt`(required, string), the prompt of the generation
    * other model supported config, see [Pollo AI API Platform](/m/pollo/pollo-v1-6)

* **img2video**

  * Generate video from image.
  * Input: `model`(object)，supports multiple models, for a detailed list, see [Pollo AI API Platform](/m/pollo/pollo-v1-6)
    * `modelBrand`(required, string), *e.g., pollo, kling-ai, runway.*
    * `modelAlias`(required, string), *e.g., pollo-v1-6, kling-v2, runway-gen-4-turbo.*
    * any of
      * `imagePath`(string) and `imageTailPath`(string)，the local image path used to generate the video.
      * `image`(string) and `imageTail`(string), the image url used to generate the video. Only image URLs are accepted; base64 is not allowed.
    * other model supported config, see [Pollo AI API Platform](/m/pollo/pollo-v1-6)

* **getTaskStatus**

  * Check generation task status, and automatically download the completed video.
  * Inputs:
    * `taskId` (string): generation task id returned by **text2video** and **img2video**