Portuni

A shared map of how your organization works – its projects, processes, areas, and principles – held as one graph that every tool and every AI agent can read. People and agents draw from the same picture instead of rebuilding context from scratch in every app.

• Website: portuni.com
• Documentation: docs.portuni.com
• License: Apache 2.0

What's in this repo

The Portuni server: a TypeScript MCP server (Streamable HTTP) backed by Turso (shared team database) or local SQLite (solo / testing), with a pluggable file-sync layer for files attached to graph nodes.

apps/
  server/    MCP/HTTP server: schema, sync engine, tools, auth (Node)
  web/       Desktop/web UI (React + Vite)
  desktop/   Tauri 2 shell that bundles server + web into Portuni.app (Rust)
sites/
  marketing/ Marketing site, portuni.com (Astro)
  docs/      Public documentation site, docs.portuni.com (Astro Starlight)
scripts/     write-scope guard, sidecar build, maintenance scripts
test/        node:test suite (no external runner)
docs/        Internal design notes and specs

Quickstart

Requires Node.js 20+ and Varlock.

git clone https://github.com/honzapav/portuni
cd portuni
npm install
npm run build
npx varlock run -- npm run dev

Server listens on http://localhost:4011. Health check: curl http://localhost:4011/health.

The full setup guide – environment variables, Turso vs local SQLite, running multiple instances, connecting MCP clients – lives at docs.portuni.com/getting-started/setup.

Project status

Portuni is alpha software in active development. The graph model, MCP tools, events, and file sync are stable enough to build on. Multi-user auth, search, additional file backends, and a proper migration framework are not built yet – manage expectations accordingly.

For the full picture and what's coming next, see Project status & roadmap.

Tests

npm test

Contributing

See CONTRIBUTING.md. Read the docs first – Portuni is built on specific concepts (POPP framework, intentional capture, graph-not-tree) and understanding them helps your contribution fit naturally.