Provides access to Google Docs API, allowing management and manipulation of documents in Google Docs, including creation, editing, and formatting of documents, handling comments, and managing document permissions.
This project is an MCP (Multi-Agent Conversation Protocol) Server for the given OpenAPI URL - https://api.apis.guru/v2/specs/googleapis.com/docs/v1/openapi.json, auto-generated using AG2's MCP builder.
pip install -e ".[dev]". If you are not using the dev container, you can run this command manually.uv:This project uses ruff for linting and formatting, mypy for static type checking, and pytest for testing.
To check for linting issues:
To format the code:
These commands are also available via the scripts/lint.sh script.
To run static analysis (mypy, bandit, semgrep):
This script is also configured as a pre-commit hook in .pre-commit-config.yaml.
To run tests with coverage:
This will run pytest and generate a coverage report. For a combined report and cleanup, you can use:
This project uses pre-commit hooks defined in .pre-commit-config.yaml. To install the hooks:
The hooks will run automatically before each commit.
The MCP server can be started using the mcp_server/main.py script. It supports different transport modes (e.g., stdio, sse).
To start the server (e.g., in stdio mode):
The server can be configured using environment variables:
CONFIG_PATH: Path to a JSON configuration file (e.g., mcp_server/mcp_config.json).CONFIG: A JSON string containing the configuration.SECURITY: Environment variables for security parameters (e.g., API keys).Refer to the if __name__ == "__main__": block in mcp_server/main.py for details on how these are loaded.
The tests/test_mcp_server.py file demonstrates how to start and interact with the server programmatically for testing.
This project uses Hatch for building and publishing. To build the project:
To publish the project:
These commands are also available via the scripts/publish.sh script.
This server cannot be installed
An MCP (Multi-Agent Conversation Protocol) Server that enables AI agents to interact with Google Docs via natural language, automatically generated using AG2's MCP builder.