Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add rules/adexltd/mcp-google-suite/cursorrulesgit clone --depth 1 https://github.com/adexltd/mcp-google-suiteWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.02122 | $0.02122 |
| Opus 5 | $0.01061 | $0.01061 |
| Sonnet 5 | $0.00424 | $0.00424 |
| Haiku 4.5 | $0.00212 | $0.00212 |
Grade A, and why
cursorrules scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
Copies of this mod
1 near-identical copy found in the catalogue:
- cursorrules — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 227 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Assume you are a Sr software engineer who has an experience in developing AI agents, experience with python.
Important Rules
- Use uv and pyproject to manage and track dependency.
- Use latest packages from python
- MCP stans for model context protocol https://modelcontextprotocol.io/introduction
- Create necessary .gitignore entries
- Update the README.md keep it minimal
- Use this as an example https://github.com/modelcontextprotocol/python-sdk?tab=readme-ov-file#core-concepts
- Do not use Fast API or other API management framework use Pure MCP eg uv add "mcp"
- use Fast MCP client
Instructions
Based on the project requirement document create me a MCP server for google drive , docs and sheets operations. use @https://github.com/modelcontextprotocol/python-sdk?tab=readme-ov-file#core-concepts as an example and for creating MCP server no need to use other frameworks like Fast API
Project Requirements Document (PRD)
Google Workspace Integration MCP Server
1. Introduction
1.1 Purpose
This document outlines the requirements for developing a Model Context Protocol (MCP) server that integrates with Google Workspace (Drive, Docs, and Sheets) to expose these capabilities as tools for Large Language Model (LLM) providers. The MCP server will serve as a bridge between LLM agents and Google Workspace data and functionality.
1.2 Scope
The MCP server will provide a standardized API for LLM agents to perform operations on Google Drive, Google Docs, and Google Sheets, including creating, reading, updating, and organizing content. The server will handle authentication, permission management, and provide options for scoping access to specific folders or the entire Drive.
1.3 Definitions, Acronyms, and Abbreviations
- MCP: Model Context Protocol - A standardized protocol for LLM tools integration
- LLM: Large Language Model
- OAuth: Open Authorization protocol
- API: Application Programming Interface
- PRD: Project Requirements Document
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2d ago First seen · 227 lines · 2,122 tokens per session scan A 861e0f4a8d76
cursorrules is a cursor rule published in the GitHub repository adexltd/mcp-google-suite (3 stars, last pushed 1y ago), licensed MIT. It adds 2,122 tokens to every session, about $0.0106 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other cursor rules, from other repositories
angular-20
This rule provides comprehensive best practices and coding standards for Angular development, focusing on modern TypeScript, standalone components, signals, and performance optimizations.
dev-standard
Apache Superset development standards and guidelines for Cursor IDE.
coolify-ai-docs
Master reference to all Coolify AI documentation in .ai/ directory.
typescript
Changes to these high-fan-out internals can affect every message, delta, element, or rerun. Keep work in them minimal, and benchmark changes with representative stress-test apps.
python_lib
Tips and guidelines specific to the development of the Streamlit Python library, not applicable to scripts and e2e tests.
specs
This directory contains product and tech specs for Streamlit features.