MCPApp

MCPApp is a lightweight, Google Apps Script‑based implementation of the Model Context Protocol (MCP) that lets AI assistants—such as Claude or Gemini CLI—fetch context, execute tools, and retrieve prompts from Google Workspace services in a secure, standardized way. By acting as a universal adapter, MCPApp solves the common problem of bridging stateless AI models with stateful external systems, enabling richer, data‑driven interactions without exposing sensitive credentials or building custom connectors for each platform.

The server exposes a REST‑like API that follows MCP’s resource, tool, and prompt conventions. Developers can register Google Sheets rows as contextual data sources, create custom “tool” endpoints that run Apps Script functions (for example, querying a spreadsheet or sending an email), and publish reusable prompts that the AI can retrieve on demand. The built‑in LockService ensures concurrency safety, while the optional lock‑disabling flag lets high‑throughput clients trade a small risk for faster responses. All interactions are authenticated via an access key, keeping the server secure yet easy to deploy in a shared Google Workspace environment.

Key capabilities include:

• Context Retrieval – Query structured data (Sheets, Docs) and return it in a format the model can ingest.
• Tool Execution – Expose arbitrary Apps Script functions as callable tools, allowing the AI to trigger workflows such as updating records or sending notifications.
• Prompt Management – Store and serve prompts that can be injected into the model’s prompt chain, supporting dynamic instruction sets.
• Concurrency Control – Built‑in locking protects against race conditions; developers can fine‑tune this for their workload.
• Google Apps Script Integration – The entire stack runs within the familiar GAS environment, eliminating deployment overhead and leveraging existing Google APIs.

Real‑world scenarios that benefit from MCPApp include:

• Data‑driven decision support – An AI assistant pulls the latest sales figures from a sheet, processes them with a custom script, and presents insights to users.
• Automated reporting – The model generates a report prompt, calls a tool that compiles data into a PDF, and emails it to stakeholders.
• Dynamic content generation – Prompts stored in the server are fetched on demand, allowing the assistant to adapt its tone or style based on user context.

By standardizing how AI models request and receive external data, MCPApp streamlines integration into existing Google Workspace workflows. It removes the need for bespoke APIs, reduces security risks through access keys and optional locking, and gives developers a single, well‑documented entry point for extending AI capabilities across sheets, docs, and custom scripts.