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MCP Integration

HitPaw now provides an MCP (Model Context Protocol) server for image and video enhancement workflows. This page focuses on the video side of the MCP integration.

This allows LLM clients such as Claude Desktop and Cursor to call HitPaw video tools directly instead of integrating the REST API by hand.

Repository: HitPaw MCP Server

What You Can Do With MCP​

With the HitPaw MCP server, an LLM client can:

  • select a suitable video model based on the input content
  • submit a video enhancement task
  • check task status and fetch the result URL
  • transfer remote files to OSS before processing
  • list available video models and their supported resolutions

The same MCP server also supports image enhancement. See the image documentation section for image-specific guidance.

Supported Video Tools​

The current video MCP workflow is built around these tools:

ToolPurpose
video_enhanceSubmit a video enhancement or super-resolution task
task_statusQuery task progress and retrieve the result URL
oss_transferTransfer a remote file to OSS and get a stable URL
oss_batch_transferTransfer multiple remote files to OSS
list_video_modelsList video enhancement models and supported scenarios

Why Use MCP Instead of Calling the API Directly​

Use MCP when you want an LLM client to orchestrate the workflow for you.

  • It reduces integration work for prompt-driven workflows.
  • It lets Claude or Cursor select a model based on the video type.
  • It keeps the enhancement flow inside the AI client your team already uses.

Use the REST API directly when you are building a product-side integration, backend service, or custom application logic.

Quick Start​

1. Set your API key​

The MCP server uses the same HitPaw API key as the standard API.

export HITPAW_API_KEY=your_api_key_here

Optional:

export HITPAW_API_BASE_URL=https://api-base.hitpaw.com

2. Run the MCP server​

Recommended:

npx @hitpaw/mcp-server

You can also install it globally:

npm install -g @hitpaw/mcp-server
hitpaw-mcp-server

Claude Desktop Configuration​

Edit the Claude Desktop configuration file:

  • macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
  • Windows: %APPDATA%\Claude\claude_desktop_config.json
{
  "mcpServers": {
    "hitpaw": {
      "command": "npx",
      "args": ["-y", "@hitpaw/mcp-server"],
      "env": {
        "HITPAW_API_KEY": "your_api_key_here",
        "HITPAW_API_BASE_URL": "https://api-base.hitpaw.com"
      }
    }
  }
}

Restart Claude Desktop after saving the configuration.

Cursor Configuration​

Edit ~/.cursor/mcp.json:

{
  "mcpServers": {
    "hitpaw": {
      "command": "npx",
      "args": ["-y", "@hitpaw/mcp-server"],
      "env": {
        "HITPAW_API_KEY": "your_api_key_here",
        "HITPAW_API_BASE_URL": "https://api-base.hitpaw.com"
      }
    }
  }
}

Example Workflow​

Typical prompt flow:

  1. The user shares a video URL with Claude or Cursor.
  2. The client calls list_video_models to determine the best model.
  3. The client calls video_enhance with the selected model and target resolution.
  4. The client calls task_status until the result is ready.
  5. The client returns the enhanced video URL.

Example request in natural language:

Please enhance this video to 1080p and keep faces stable:
https://example.com/video.mp4

Environment Variables​

VariableRequiredDefaultDescription
HITPAW_API_KEYYesNoneHitPaw API key
HITPAW_API_BASE_URLNohttps://api-base.hitpaw.comAPI service base URL

When To Use MCP​

MCP is a good fit when:

  • you want to trigger video enhancement from Claude or Cursor
  • your workflow is prompt-first rather than app-first
  • you want model selection and task polling handled by the AI client

If you are integrating HitPaw into your own product or backend, start with the API Reference instead.

Ready to Start?

Get started by Purchasing an API Key Now to unlock full access to the HitPaw Enhancement API.