awesome-workspace

This repository functions as an aggregated collection of resources related to Google Workspace and the Model Context Protocol (MCP). It does not appear to run its own MCP server, but rather points you to other projects and examples in the MCP ecosystem. To use the materials here, browse the linked projects (such as Gmail MCP Server implementations, GDrive MCP Servers, and other related tooling) to discover MCP-enabled tools you can deploy in your environment. When you identify a project you want to experiment with, follow that project’s own installation and usage instructions to run its MCP server or integration in your stack.

If you’re new to MCP, start by exploring examples that align with your goals (Google Workspace integrations, document actions, or data workflows) and then replicate the setup in your own environment using the target project’s provided commands and configuration options. This repository serves as a curated index to those resources rather than a standalone executable MCP server.

Prerequisites:

• Git is installed on your machine.
• Access to the internet to clone repositories and install dependencies as described by each linked project.

Step-by-step:

1. Review the README to identify specific MCP server projects you want to try (e.g., Gmail MCP Server, GDrive MCP Server, MCP YouTube Sheets).
2. Clone this repository to your local machine: git clone https://github.com/your-organization/awesome-workspace.git cd awesome-workspace
3. Open the links to the individual MCP server projects in the list and follow their installation guides. Typical steps you may encounter include:
   • Installing Node.js dependencies (npm install) for Node-based MCP servers.
   • Installing Python packages (pip install -r requirements.txt) for Python-based MCP servers.
   • Building or starting Docker containers if the project provides a docker-compose.yml or docker run instructions.
   • Setting up credentials and API access (OAuth credentials for Google Workspace, API keys, or service account files) as required by the specific project.
4. Configure environment variables as required by the chosen project (e.g., client IDs, client secrets, tokens). Use the project’s documentation to determine the exact env vars.
5. Start the MCP server according to the selected project’s instructions and verify it’s reachable via its API endpoints or web UI.

Important tips:

• This repository acts as a curated index of resources related to Google Workspace and the Model Context Protocol, rather than hosting a runnable MCP server by itself.
• Each linked project may have its own prerequisites (OAuth scopes, service account permissions, webhook configurations). Ensure you review and grant the necessary permissions in your Google Cloud Console or provider account.
• If you plan to deploy to production, consider setting up proper secret management for credentials, rotating API keys, and securing webhook endpoints.
• Some projects may offer Docker-based deployment; if you’re new to Docker, start with the containerized instructions before attempting a full, manual setup.
• Keep an eye on version compatibility between MCP tooling and Google Workspace APIs, as updates can introduce breaking changes.