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Show HN: OpenLivery – open-source multi-tenant WhatsApp agents for agencies

OpenLivery, an open-source multi-tenant platform for agencies to build and manage AI agents for clients, was released on GitHub. The platform supports WhatsApp and web chat channels, offers bring-your-own OpenAI and Anthropic keys, and includes features such as multimodal capabilities, knowledge base with semantic retrieval, custom HTTP tools, and MCP server integration. It is designed for self-hosting with one command and provides documentation in English and Spanish.

read5 min views1 publishedSep 7, 2026
Show HN: OpenLivery – open-source multi-tenant WhatsApp agents for agencies
Image: Michielbdejong (auto-discovered)

The open-source, white-label platform for agencies to build, run and manage AI agents for their clients.

Documentation · Documentación · Quick start · Self-hosting · Discussions

OpenLivery is a multi-tenant workspace where an agency creates AI agents for its clients, gives each client a branded portal, and talks to end users over WhatsApp or an embeddable web chat widget. Bring your own OpenAI / Anthropic keys and self-host the whole thing with one command.

Full documentation lives in docs/. Every guide is written twice: English and Spanish, same filename under each.

Guide What it covers
Getting started Run the stack with Docker and create your first agency
Configuration Environment variables, secrets, ports and the gateway
Architecture The services, the data model and tenant isolation
Self-hosting Deploy to a server, back up, upgrade and troubleshoot
Contributing Run the project locally, tests and conventions
Push notifications Optional, provider-agnostic notifications for the mobile app
WhatsApp Cloud API Connect a number with the official Meta API, end to end

Agentsdocs

  • ✅ Instructions, personality, per-client & per-agent context, timezone, and temperature / max-tokens / memory controls
  • ✅ Multimodal capabilities: image recognition (vision) andaudio transcription for incoming media
  • ✅ Creation wizard with a live token counter and industry starter templates

Knowledge basedocs

  • ✅ Manual context, structured Q&A pairs and PDF upload, with embedding-based semantic retrieval (keyword fallback)
  • ✅ Portable JSON embeddings — no database extension required

AI providersdocs

  • ✅ Bring-your-own OpenAI (Responses API) andAnthropic (Messages API) keys — agency-level, encrypted, and validated when saved
  • ✅ Any OpenAI-compatible endpoint via per-connection base URL + model

Custom toolsdocs

  • ✅ Per-agent HTTP tools : any REST endpoint with path/query/body parameters, encrypted auth headers and an SSRF guard
  • MCP servers (Streamable HTTP or SSE) with test-before-save connection checks and cached tool discovery
  • ✅ Tool usage recorded per reply and surfaced in the playground, including failure details

ChannelsWhatsApp Cloud API · WhatsApp QR · Web widget

  • WhatsApp Cloud API (official Meta API) — bring your own Meta app credentials, signed webhooks, per-client number
  • WhatsApp QR through whatsmeow — QR link, per-client number, persistent session that reconnects on its own
  • ✅ Embeddable web chat widget for any website
  • 🚧 Instagram DM, Facebook Messenger (planned)

OperationsInbox · Client portal · Dashboard

  • ✅ Unified Inbox with server-side search, filter tabs, unread tracking, pagination and human takeover
  • ✅ Per-client portal with its own login and Inbox, optionally served under the client'sown custom domain (DNS-verified, automatic HTTPS)
  • Dashboard with activity, top agents, token usage by model and a date-range filter
  • ✅ Agency white-label (name, identifier, color, logo)

Three services plus PostgreSQL, orchestrated by Docker Compose:

App Stack Role
apps/api FastAPI · SQLAlchemy · Alembic REST API, data model, AI/knowledge/provider services
apps/web Next.js · React · TypeScript · Tailwind Agency dashboard, client portal, playground, widget
apps/whatsapp Go · whatsmeow WhatsApp Web bridge (stateful sessions)

All data lives in PostgreSQL; provider keys and WhatsApp sessions are encrypted at rest. Every query is scoped by agency_id for tenant isolation, and public endpoints (sign-in and the web widget) are rate-limited per client IP. A Caddy gateway serves the app and API from a single origin (/api/* → backend).

Read more in the architecture guide.

Requires Docker (Desktop or Engine + Compose plugin).

git clone https://github.com/sarrazola/openlivery.git
cd openlivery
./scripts/generate-docker-env.sh   # random secrets in .env.docker (gitignored)
make up                            # build, start, migrate

Then open http://localhost:3000 (API docs at http://localhost:8000/docs). Ports clashing? API_PORT=8001 WEB_PORT=3001 DB_PORT=5433 make up. Prefer not to build? make pull runs the prebuilt images published to GHCR.

The full walkthrough — first agency, provider keys, agents, knowledge and channels — is in the getting started guide. Deploying to a public server (reverse proxy, TLS, backups) is covered in self-hosting.

apps/
  api/         FastAPI backend (app/, migrations/, tests/)
  web/         Next.js frontend (app/, components/, lib/, types/)
  whatsapp/    whatsmeow WhatsApp bridge (Go)
  mobile/      Optional Expo app for the businesses you serve (unbranded)
docs/          Self-hosting and operations guide
scripts/       Helper scripts (generate-docker-env.sh)
Makefile       Common commands (make help)
docker-compose.yml

apps/mobile is an optional Expo app: the inbox a business you serve carries in their pocket, with conversations, takeover, replies, photos and voice notes. It is not installed with the platform and the server does not need it — nobody running OpenLivery has to build or deploy it to have everything working.

It deliberately carries no brand: no name, no logo, no bundle identifier, no preset pointing at any hosted service. What ships is a working app and the machinery to make it yours — put your identity in a brand file, build, and publish it under your own name from your own developer account. The whole checklist, including why you publish it rather than us, is in apps/mobile/WHITELABEL.md.

Run the project locally, the test suites and the conventions are documented in the contributing guide. In short: all code, identifiers, comments and docs are in English; end-user UI is localized (English default, Spanish) through the typed i18n system in apps/web/lib/i18n.

MIT.

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