Qamera AI
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Setup

Configure Cursor, Claude Desktop, or any MCP client to connect to Qamera AI. Step-by-step instructions with copy-paste configurations.

Prerequisites

Before configuring your AI tool, you need:

  1. A Qamera AI account — Sign up at qamera.ai
  2. An API key — Generate one from your account settings

Getting Your API Key

  1. Log in to Qamera AI
  2. Navigate to Settings in your workspace
  3. Find the API Keys section
  4. Click Generate New Key and copy the value

Keep your API key secure. Do not share it or commit it to version control.

Cursor (Recommended)

Cursor supports MCP via SSE (Server-Sent Events) transport. The Qamera AI MCP server is hosted and ready to use — no local installation required.

Configuration

Create or edit .cursor/mcp.json in your project root:

{
  "mcpServers": {
    "qamera-ai": {
      "url": "http://162.55.224.224:3002/mcp",
      "transport": { "type": "sse" },
      "headers": {
        "Authorization": "Bearer YOUR_QAMERA_AI_API_KEY"
      }
    }
  }
}

Replace YOUR_QAMERA_AI_API_KEY with your actual API key.

Activate

  1. Save the configuration file
  2. Restart Cursor to load the new MCP server
  3. Open the AI chat and start using Qamera AI tools

You can verify the connection by asking: "List my products using Qamera AI"

Claude Desktop

Claude Desktop uses stdio transport, which requires running the MCP server locally.

Installation

# Clone the MCP server repository
git clone https://github.com/shorts-lab-ai/mcp-server-for-shorts-lab.git
cd mcp-server-for-shorts-lab

# Install dependencies
npm install

# Build
npm run build

Configuration

Add the server to your Claude Desktop configuration file:

macOS: ~/Library/Application Support/Claude/claude_desktop_config.json

Windows: %APPDATA%\Claude\claude_desktop_config.json

{
  "mcpServers": {
    "qamera-ai": {
      "command": "node",
      "args": ["path/to/mcp-server-for-shorts-lab/dist/index.js"],
      "env": {
        "QAMERA_AI_API_BASE_URL": "https://qamera.ai",
        "QAMERA_AI_API_KEY": "YOUR_QAMERA_AI_API_KEY"
      }
    }
  }
}

Replace path/to/mcp-server-for-shorts-lab with the actual path to your cloned repository, and YOUR_QAMERA_AI_API_KEY with your API key.

Activate

  1. Save the configuration file
  2. Restart Claude Desktop
  3. Look for the MCP tools icon in the chat interface

Other MCP Clients

Any MCP-compatible client can connect to the hosted Qamera AI MCP server using SSE transport.

Connection Details

  • Server URL: http://162.55.224.224:3002/mcp
  • Transport: SSE (Server-Sent Events)
  • Authentication: Include one of these headers:
    • Authorization: Bearer YOUR_API_KEY
    • X-Api-Key: YOUR_API_KEY

Health Check

Verify the server is running:

curl http://162.55.224.224:3002/health

A successful response confirms the server is available and ready to accept connections.

Running Locally (Optional)

If you prefer to run the MCP server on your own machine:

git clone https://github.com/shorts-lab-ai/mcp-server-for-shorts-lab.git
cd mcp-server-for-shorts-lab
npm install
npm run build
npm run start:http

The server will start at http://localhost:3002. Update your client configuration to use http://localhost:3002/mcp as the server URL.

Create a .env file for configuration:

QAMERA_AI_API_BASE_URL=https://qamera.ai
PORT=3002

Next Steps