Frequently Asked Questions about UBOS MCP Server for Google Drive

Q: What is an MCP Server? A: MCP (Model Context Protocol) server acts as a bridge, allowing AI models to access and interact with external data sources and tools. UBOS MCP Server for Google Drive provides Google Drive access for AI models.

Q: What file types are supported by the Google Drive MCP server? A: The server supports all file types in Google Drive. Google Workspace files (Docs, Sheets, Presentations) are automatically converted to Markdown, CSV, and Plain text, respectively.

Q: How does the Google Drive MCP server handle authentication? A: It uses OAuth 2.0 for secure authentication. You need to configure an OAuth client ID in your Google Cloud project and provide the credentials to the server.

Q: Can I use this MCP server with the UBOS desktop app? A: Yes, you can integrate this server with the desktop app by adding its configuration details (command and arguments) to your app’s server configuration.

Q: Is the UBOS MCP Server for Google Drive free to use? A: The MCP server itself is licensed under the MIT License, making it free to use, modify, and distribute. However, using it within the UBOS platform might require a UBOS subscription, depending on your usage.

Q: How secure is the connection to Google Drive? A: The connection is secured using Google’s OAuth 2.0 protocol, which provides a secure and standardized way to authorize access to Google Drive data without sharing your credentials directly with the server.

Q: What if I don’t want to use Docker? A: You can use NPX to run the server directly without Docker.

Q: What scopes are required for OAuth? A: You need to add the https://www.googleapis.com/auth/drive.readonly OAuth scope to your OAuth consent screen.

Q: Can the MCP server upload to Google Drive? A: No, this MCP server provides readonly access to Google Drive.

Q: What is UBOS Platform? A: UBOS is a Full-stack AI Agent Development Platform focused on bringing AI Agent to every business department. Our platform helps you orchestrate AI Agents, connect them with your enterprise data, build custom AI Agents with your LLM model and Multi-Agent Systems.