What are the prerequisites?
Node.js v14+, npm, and a Google Cloud Platform account with the Drive API and Docs API enabled.
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A Model Context Protocol (MCP) server for the Google Docs API, enabling language models to search, create, append to, and update Google Docs programmatically.
Install dependencies with npm install, set up Google OAuth 2.0 credentials (save as credentials.json), run node get-refresh-token.js for authorization, build the server with npm run build, then start with npm start or node build/index.js. Optionally build the Extism plugin for direct testing.
Node.js v14+, npm, and a Google Cloud Platform account with the Drive API and Docs API enabled.
Create an OAuth 2.0 credential of type “Desktop application” in the Google Cloud Console, download the JSON, and save it as `credentials.json` in the project root.
Run `npm start` or directly `node build/index.js` after building the project. The server starts as an MCP endpoint.
Yes, build it first (`cd extism-plugin && npm install && npm run build`), then call it via the Extism CLI with the appropriate Wasm arguments and an access token.

Exact, shared memory for AI agents: a hierarchical database where totals always add up, every write is attributed to the agent and person behind it, and any figure traces back to its source file. Agents create databases,

Orcha is a unified context layer for AI tools and agents. It stores and indexes and exposes organizational, team, or individual knowledge. Files, structured databases, and connected sources live in one workspace, and age
Groundwork: company memory for your AI tools. Docs public. Source closed. Public proof needs no account.
Project context your AI can query through MCP — with source evidence.

Model Context Protocol Servers
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