tanaikech/ggsrun

Description and use

**Brief Summary (2‑3 sentences)**
tanaikech/ggsrun is a high‑performance Go‑based CLI and Model Context Protocol (MCP) server that lets LLM/AI agents interact directly with Google Drive and execute Google Apps Script (GAS) on‑the‑fly. It handles conflict resolution, recursive transfers, and full Drive infrastructure management, providing a standardized bridge between AI assistants and real‑world tools and data.

**Value**

• **Unified AI‑to‑tool interface**: By exposing Drive operations and dynamic GAS execution through the MCP, developers can give LLMs concrete, secure access to files, scripts, and automation without custom glue code.
• **Speed & scalability**: Written in Go, the server delivers low‑latency, concurrent handling of large Drive workloads, making it suitable for production‑grade AI workflows.
• **Standardized protocol**: MCP offers a vendor‑agnostic contract, simplifying the integration of multiple AI agents or services while keeping the underlying Drive logic encapsulated.

**Practical Adoption Path**

1. **Prototype** – Clone the repo, run the provided CLI locally, and point an LLM (e.g., OpenAI, Anthropic) to the MCP endpoint using the supplied SDK or HTTP calls.
2. **Integrate** – Replace ad‑hoc Drive calls in your agent’s code with MCP requests; leverage the built‑in conflict policies and recursive transfer flags to match your business rules.
3. **Deploy** – Containerize the Go server (Dockerfile is included), push to your orchestration platform (K8s, Cloud Run, etc.), and configure OAuth scopes for the service account that will access Drive.
4. **Scale & Secure** – Enable TLS, add rate‑limiting, and optionally plug in your own authentication layer; the server’s stateless design lets you horizontally scale as demand grows.

**Production Readiness**

• **Activity & Community**: 167 stars, 18 forks, recent commits (as of 2026‑06‑24), and a well‑defined issue/PR workflow indicate an active maintainer base.
• **Maturity**: The Go implementation, comprehensive CLI, and explicit MCP spec demonstrate a production‑grade codebase; the project already supports key Drive features (conflict policies, recursive ops) out of the box.
• **Risks**: Licensing and long‑term security maintenance still require a final review, but no major metadata or vulnerability flags have been identified. Overall, the project is positioned as a strong OSS candidate for pilots and full‑scale deployments.

Use in a workflow

tanaikech/ggsrun helps connect AI assistants to real tools and data through a standard protocol.

• connect AI agents to tools
• ship Model Context Protocol servers
• standardize integrations

Limitations and review notes

High for an OSS candidate: recent activity, adoption, and ecosystem signals are strong enough for a serious pilot.