How are my Google credentials stored?

Tokens are stored securely using your operating system's native keyring, such as macOS Keychain, Windows Credential Locker, or the Linux Secret Service API.

Can I use the full document URL to read content?

Yes, the skill automatically extracts the document ID from a full Google Docs URL, so you don't have to manually copy the ID string.

Do I need to set up a full MCP server to use this?

No, this is designed as a lightweight alternative that uses standalone OAuth authentication and Python scripts, making it easier to deploy without complex server infrastructure.

Does this skill require a Google Workspace account?

Yes, this skill requires a Google Workspace account. Personal @gmail.com accounts are currently not supported for this specific implementation.

Google Docs Integration

Name: Google Docs Integration
Author: sanjay3290

bysanjay3290

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Content Management

Manages Google Documents directly within your AI coding workflow to create, search, and edit content seamlessly.

About

This skill provides a lightweight, standalone integration for Google Docs, allowing AI agents to interact with documents without requiring a full Model Context Protocol (MCP) server setup. It enables users to automate document creation, retrieve text content using URLs or IDs, and perform precise text manipulations like appending, inserting, or replacing content. It is particularly useful for developers who need to generate meeting notes, technical documentation, or project plans directly from their terminal or AI workspace while maintaining secure OAuth authentication.

Key Features

Perform precise text edits including append, insert, and replace-text operations
Search for existing documents by title with configurable result limits
Secure local token management using system-level keyrings (macOS, Windows, Linux)
Create new documents with optional markdown-style initial content
Extract document text via direct ID or full Google Docs URL
37 GitHub stars

Use Cases

Updating shared team documents with automated status reports or log summaries
Automating the creation of project plans and meeting notes during coding sessions
Retrieving context from existing technical documentation to inform AI coding tasks

About

Key Features

Perform precise text edits including append, insert, and replace-text operations
Search for existing documents by title with configurable result limits
Secure local token management using system-level keyrings (macOS, Windows, Linux)
Create new documents with optional markdown-style initial content
Extract document text via direct ID or full Google Docs URL
37 GitHub stars

Use Cases

Updating shared team documents with automated status reports or log summaries
Automating the creation of project plans and meeting notes during coding sessions
Retrieving context from existing technical documentation to inform AI coding tasks