What are the prerequisites for using this server?
You need Node.js v16 or higher, npm or yarn, a Google Cloud Project with the Google Drive API enabled, and a Google Workspace or personal Google account.
@felores
基本信息
Efficient implementation of the Google Drive MCP server
使用下面的配置,将此服务器添加到你的 MCP 客户端。
{
"mcpServers": {
"gdrive-mcp-server-felores": {
"command": "node",
"args": [
"dist/index.js",
"auth"
]
}
}
}工具列表暂未提供
当前收录暂时没有可展示的工具列表,不代表服务没有工具。请查阅项目文档了解支持的能力。
工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。
A Model Context Protocol (MCP) server that integrates with Google Drive, enabling AI models to search, list, and read files from Google Drive. It is intended for developers building AI applications that need to access Google Drive content.
Install dependencies, build the project, then set up Google Cloud credentials and run node dist/index.js auth to authenticate via OAuth. Start the server with node dist/index.js. For integration with a desktop MCP app, add a JSON configuration block specifying the command, arguments, and environment variables for the OAuth key files.
gdrive_search (file search) and gdrive_read_file (read file contents by ID)credentials directoryYou need Node.js v16 or higher, npm or yarn, a Google Cloud Project with the Google Drive API enabled, and a Google Workspace or personal Google account.
After placing your downloaded OAuth client JSON file in `credentials/gcp-oauth.keys.json`, run `node dist/index.js auth` and complete the OAuth flow in your browser. Credentials are saved to `credentials/.gdrive-server-credentials.json`.
The server requests read‑only access to Google Drive (scope `https://www.googleapis.com/auth/drive.readonly`).
All sensitive credentials are stored in the `credentials` directory, which is excluded from version control. The OAuth keys and token files are kept locally.
Google Docs become Markdown, Google Sheets become CSV, Google Presentations become plain text, Google Drawings become PNG, text/JSON files are returned as UTF‑8 text, and other files are Base64 encoded.
A MCP server providing realistic browser-like HTTP request capabilities with accurate TLS/JA3/JA4 fingerprints for bypassing anti-bot measures. It also supports converting PDF and HTML documents to Markdown for easier processing by LLMs.
📄 The PDF intelligence layer for AI agents — Agent Document Twin, evidence-first extraction, visual crops, OCR provenance, trust reports, and benchmark-gated releases. MCP server for Claude, Cursor, VS Code, and any MCP client.
A Model Context Protocol (MCP) server for platform-agnostic file capabilities, including advanced search/replace and directory tree traversal
Manage your Hevy workouts, routines, folders, and exercise templates. Create and update sessions faster, organize plans, and search exercises to build workouts quickly. Stay synced with changes so your training log is always up to date.
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