python-sdk vs google_workspace_mcp
python-sdk: The MCP Python SDK provides a robust implementation of the Model Context Protocol, enabling developers to build secure, standardized servers that expose data and functionality to LLM applications. It also includes a client library for connecting to any MCP server, supporting various standard transports like stdio, Streamable HTTP, and SSE.; google_workspace_mcp: This production-ready MCP server enables full natural language control over Google Workspace services like Calendar, Drive, Gmail, Docs, Sheets, Slides, Forms, Tasks, and Chat through MCP clients, AI assistants, and developer tools. It is the most feature-complete Google Workspace MCP server, now supporting Remote OAuth2.1 multi-user operation and one-click Claude installation.
TL;DR
- You want the official, MIT-licensed reference Python SDK maintained directly by the Model Context Protocol project.
- You need full low-level control over MCP primitives (resources, prompts, tools, sampling) and standard transports (stdio, SSE, Streamable HTTP).
- You want higher-level conveniences like automatic client composition or less decorator boilerplate; FastMCP wraps the protocol with extra ergonomics.
- You are exposing an existing GraphQL or FastAPI backend where a gateway or adapter (Grafbase or FastAPI-MCP) requires no manual tool code.
- You want one server for Gmail, Drive, Calendar, Docs, Sheets, Slides, Forms, Tasks and Chat instead of one per service.
- Several people will use it: it supports multi-user OAuth 2.0 and 2.1 with bearer tokens.
- You want to limit exposure with tool tiers such as `--tool-tier core`.
- You only need Sheets: a focused server exposes fewer tools and less account access.
- You cannot create your own Google Cloud OAuth credentials: setup requires them.
- Giving an assistant access to Gmail and Drive is not acceptable in your organisation.
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