Nubase – an open-source back end/deploy layer for AI-written apps

Nubase, an open-source AI-native backend and deploy layer, launched to let coding agents turn AI-written code into live apps in minutes. The platform bundles database, auth, storage, functions, AI gateway, memory, and cron into a single self-hostable service, enabling agents to deploy apps through MCP tools without separate hosting accounts.

English · 简体中文 /OtterMind/Nubase/blob/main/README.zh-CN.md Turn AI-written code into real apps. Nubase is an open-source, AI-native backend and deploy layer that a coding agent drives directly — so a generated app goes live in minutes. Eight capability modules in one self-hostable service: Database, Auth, Storage, Assets, Functions, AI Gateway, Memory, and cron . An agent can model the data Database + Auth , deploy backend logic Functions , publish the generated frontend to a public CDN Assets , and schedule recurring work cron — all through MCP tools, with no separate hosting account. Supabase-style where it makes sense Postgres, REST, JWTs, RLS, object storage, a Studio dashboard , plus first-classMemoryand anMCPsurface built for AI coding agents. From your project folder, run: npx -y nubase cli@latest install-skills That single command: - 📚 installs the Nubase skills for both Claude Code and Codex , - 🔌 wires up the MCP server config, and - 🔐 opens a browser to authorize and pick your project. Then: Claude Code — restart it in this folder, run /mcp , and confirm nubase is connected. Codex — it's added to ~/.codex/config.toml ; just start Codex. This connects your agent to a Nubase instance a hosted one, or your own — spin one up in step 2 . Point the CLI at any instance with: npx -y nubase cli@latest install-skills \ --studio-url https://studio.example.com \ --nubase-url https://api.example.com The all-in-one Docker image bundles PostgreSQL + Redis + the backend + Studio : docker run -d --name nubase \ -p 9999:9999 -p 5432:5432 \ -v nubase data:/data \ <your-namespace /nubase:latest Studio → http://localhost:9999/studio http://localhost:9999/studio — create an account, create a project, click Provision to initialize its database. API → http://localhost:9999 http://localhost:9999 the Studio UI is bundled into the backend and served on the same port First-boot secrets are generated into the /data volume; keep the volume to retain your projects. For a real deployment with stable secrets, see Self-host with Docker . Your agent can now operate Nubase directly through MCP tools — inspect schema, create tables, run SQL, manage auth & storage, deploy edge functions, publish a frontend to the public CDN, schedule cron jobs , and read/write durable memory . Try asking: "Create a todos table with RLS, deploy an edge function that returns the open count, publish a one-page UI to Assets that calls it, and remember the deployment." See Deploy an AI-generated app /OtterMind/Nubase/blob/main/docs/deploy-ai-generated-apps.md for the full generate → live walkthrough. The single all-in-one image is everything you need to run Nubase on your own box — one line, no compose file, no external services . Try it auto-generated secrets, kept in the volume : docker run -d --name nubase -p 9999:9999 -p 5432:5432 \ -v nubase data:/data <your-namespace /nubase:latest Production pin stable secrets so encrypted project credentials survive restarts : docker run -d --name nubase -p 9999:9999 -p 5432:5432 \ -v nubase data:/data \ -e PGRST ENCRYPTION MASTER KEY="$ openssl rand -base64 32 " \ -e METADATA SERVICE ROLE KEY="$ openssl rand -base64 48 " \ <your-namespace /nubase:latest Everything else is configured via environment variables — Postgres, Redis, S3/R2 storage, SMTP, OAuth, and LLM providers. See docs/docker-all-in-one.md /OtterMind/Nubase/blob/main/docs/docker-all-in-one.md for the full list and a multi-architecture amd64 + arm64 note. Replace <your-namespace with the Docker Hub namespace the image is published under. AI-native applications need more than CRUD. They need user memory, retrieval, auth, storage, database APIs, and project isolation from day one. Without that backend layer, every AI coding session produces another demo that still needs weeks of infrastructure work. Supabase is excellent, but its open-source self-hosted stack is designed around a single project. Nubase is built for AI teams and self-hosters who want one Studio, one backend service, and many isolated AI projects on their own infrastructure — with three opinionated additions: Memory is a first-class primitive — durable memory, entity extraction, history, and hybrid retrieval are built in, not bolted on as a separate vector-store script. AI coding gets a real backend target — agents create tables, call REST APIs, write memory, and inspect schema through MCP-friendly tools. Self-hosting supports many projects — a single control plane provisions and routes to multiple isolated project databases. 🗄️ Database — one isolated PostgreSQL per project; a PostgREST-compatible /rest/v1 API select/filter/order/paginate/insert/update/upsert/delete ; per-project JWT secrets, roles, and schema cache; Row Level Security with JWT claims. 🔐 Auth — Supabase-style signup/login and refresh-token rotation; MFA/TOTP, OTP & magic links, anonymous sign-in; OAuth Google / GitHub / WeChat and SAML SSO; per-project anon / authenticated / service role tokens. 📦 Storage — S3-compatible Cloudflare R2 / AWS S3 / MinIO ; public/private buckets, signed URLs, size & MIME controls; optional S3 Vectors for large document/asset workloads. 🌐 Assets static CDN — publish a generated frontend: per-project public static assets served at /assets/v1/ with Cache-Control/ETag/304 semantics; per-project default cache policy and custom CDN domain; agents publish directly over MCP assets upload . ⚡ Functions — deploy backend logic as edge functions served at /functions/v1/ ; per-function secrets, invocation logs, rate limits, verify jwt ; local executor or Cloudflare Workers for Platforms; agents scaffold/deploy/invoke over MCP functions deploy . 🤖 AI Gateway — OpenAI- and Anthropic-compatible endpoints with per-project keys and token/cost usage tracking. 🧠 Memory — Mem0-style memory API; LLM-powered fact extraction ADD/UPDATE/DELETE/NONE ; hybrid retrieval over pgvector + Postgres full-text + entity boost; entity store and append-only history. Works with OpenAI, Anthropic, and OpenAI-compatible providers. ⏰ Scheduled Jobs cron — recurring jobs that invoke an edge function or a named database function on a crontab schedule, run by the control plane with run history; managed over MCP cron create . 🧰 AI Coding & Agents — an MCP bridge nubase cli for schema inspection, SQL execution, RLS export, project init, and memory; one consistent project-token model across Auth, REST, Storage, and Memory. 🎛️ Studio — a Next.js dashboard for projects, SQL with execution history , users, storage, and the memory explorer. Full comparison as a table including Supabase Cloud | Area | Supabase Cloud | Supabase self-hosted | Nubase | |---|---|---|---| | Multi-project dashboard | Yes | No mimics one project | Yes | | Project isolation | Dedicated instance | One local project | Dedicated Postgres DB per project | | Database API | PostgREST | PostgREST | PostgREST-compatible Java | | Auth | Yes | Yes | Supabase-style Auth | | Storage | Yes | Yes | S3/R2-compatible | | AI memory | Not a core primitive | Not a core primitive | Built-in Memory pillar | | AI coding backend target | General primitives | General primitives | Memory + REST + MCP + Studio | | Deploy a generated app | App + separate hosting/Functions/cron | Self-managed stack | Frontend Assets + backend Functions + cron, one platform | | Edge Functions | Yes | Available in stack | Gateway + executor local / Cloudflare WfP | | Realtime | Yes | Available in stack | Not yet | Nubase has two database layers: Metadata database — platform users, project configs, encrypted project credentials, ownership, platform settings, SQL snippets, and execution records. Project databases — each project gets its own PostgreSQL database with auth tables, storage metadata, memory tables, and application tables. Requests use a two-token model: apikey identifies the project + role anon / authenticated / service role , and Authorization: Bearer <jwt identifies the end user for RLS and memory ownership. A request filter resolves the project from the apikey , routes JDBC to the correct project database, and sets the request context. Requirements: Java 17, Maven, Docker, Node.js + pnpm. 1. Start Postgres 15 + pgvector docker compose -f pg-docker-compose.yml up -d 2. Required secrets export PGRST ENCRYPTION MASTER KEY="$ openssl rand -base64 32 " export METADATA SERVICE ROLE KEY="replace-with-a-long-random-admin-token" export OPENAI API KEY="sk-..." optional, only for LLM-powered Memory 3. Backend → http://localhost:9999 mvn spring-boot:run 4. Studio → http://localhost:3000 cd frontend && pnpm install && pnpm dev:studio To build the all-in-one image yourself: docker build -f Dockerfile.all-in-one -t nubase:local . Write and search memory: curl -X POST http://localhost:9999/mem/v1/memories \ -H "apikey: $NUBASE SERVICE KEY" -H "Content-Type: application/json" \ -d '{"userId":"user-42","messages": {"role":"user","content":"I prefer steak over sushi and my dog is named Mochi."} }' curl -X POST http://localhost:9999/mem/v1/search \ -H "apikey: $NUBASE SERVICE KEY" -H "Content-Type: application/json" \ -d '{"userId":"user-42","query":"what food do they like?"}' Use the REST API after creating a todos table : curl "http://localhost:9999/rest/v1/todos?select= " -H "apikey: $NUBASE ANON KEY" curl -X POST "http://localhost:9999/rest/v1/todos" \ -H "apikey: $NUBASE SERVICE KEY" -H "Content-Type: application/json" \ -d '{"text":"Ship the first open-source release"}' Getting started /OtterMind/Nubase/blob/main/docs/getting-started.md Deploy an AI-generated app generate → live /OtterMind/Nubase/blob/main/docs/deploy-ai-generated-apps.md Connect agents Claude / Codex / Cursor /OtterMind/Nubase/blob/main/docs/agent-connect.md MCP & agent guide /OtterMind/Nubase/blob/main/docs/mcp.md Edge Functions /OtterMind/Nubase/blob/main/docs/edge-functions.md · Assets static CDN /OtterMind/Nubase/blob/main/docs/assets.md · Scheduled Jobs cron /OtterMind/Nubase/blob/main/docs/scheduled-jobs.md nubase cli usage /OtterMind/Nubase/blob/main/docs/nubase-cli-usage.md All-in-one Docker image /OtterMind/Nubase/blob/main/docs/docker-all-in-one.md Architecture /OtterMind/Nubase/blob/main/docs/architecture.md Product overview /OtterMind/Nubase/blob/main/docs/product-overview.md Supabase comparison /OtterMind/Nubase/blob/main/docs/supabase-comparison.md Nubase is early-stage but all eight modules Database, Auth, Storage, Assets, Functions, AI Gateway, Memory, cron plus Studio and the MCP bridge are in place. Not yet implemented: Realtime and operational extras like backups/PITR, HA, and enterprise SSO/SCIM. Review the admin/management endpoints before exposing a server to the public internet. Contributions and issues are welcome — see CONTRIBUTING.md /OtterMind/Nubase/blob/main/CONTRIBUTING.md and SECURITY.md /OtterMind/Nubase/blob/main/SECURITY.md . This is an early public release, so feedback shapes what comes next. 🙌