Documentation MCP Server

The Qloo Documentation Model Context Protocol (MCP) server lets AI tools such as Cursor, Windsurf, and Claude use Qloo’s documentation as a source of context. Through this MCP server, those tools can search the docs, answer questions about Qloo, and generate example code based on documented functionality. It connects to the documentation only, not directly to the Qloo API.

Use the Documentation MCP server to explore the full range of Qloo API capabilities, understand endpoints and parameters, and get guidance for building custom integrations that use the full flexibility of the Qloo API.

Qloo also provides the Qloo MCP Server, which gives AI tools access to Qloo's data. To compare the two, see MCP Servers.

What Is MCP?

Model Context Protocol (MCP) is an open standard that allows AI applications to securely access external data sources and tools. The Qloo Documentation MCP server provides AI agents with:

• Documentation access for Qloo products and features
• Documentation search capabilities
• Usage guidance for Qloo APIs and integrations
• Code generation assistance based on Qloo docs and examples

Set Up the Qloo Documentation MCP Server

Qloo hosts a remote documentation MCP server at https://docs.qloo.com/mcp. Configure your AI development tools to connect to this server so they can retrieve context from the Qloo documentation.

claude mcp add --transport http qloo-docs https://docs.qloo.com/mcp

{
  "mcpServers": {
    "qloo-docs": {
      "url": "https://docs.qloo.com/mcp"
    }
  }
}

{
  "mcpServers": {
    "qloo-docs": {
      "url": "https://docs.qloo.com/mcp"
    }
  }
}

Test Your MCP Setup

Once configured, you can test your MCP server connection:

1. Open your AI tool (Cursor, Windsurf, Claude, etc.)

2. Start a new chat with the AI assistant

3. Ask about Qloo documentation, for example:

   • "How do I get recommendations from the Insights API?"
   • "What filters can I use with /v2/insights?"
   • "Which parameters are available for each entity type?"
   • "Write a Python example that calls /v2/insights for movie recommendations."

The AI should now be able to use the Qloo documentation through the MCP server as a reference for answering questions, explaining endpoints, and generating example integrations. It does not connect directly to the Qloo API or your Qloo account through this MCP server.