Open Source App Cloud Marketplace

Webhooks, cron schedules, and app events trigger chains of nodes that fetch, transform, and route data: n8n is a workflow automation platform built around a visual, node-based editor. It ships with 400+ built-in integrations covering databases like Postgres, SaaS tools like Slack and HubSpot, and every major AI provider. When a pre-built node does not exist, the HTTP Request node calls any REST API, and the Code node runs JavaScript or Python inline, so you are never blocked by a missing connector. Workflows execute as directed graphs with branching, loops, error handling, and sub-workflows, and every run is logged for inspection and replay during debugging. It also includes LangChain-based nodes for building AI agents with tool calling and memory. Self-hosting on RepoCloud gives you unlimited workflow executions with no per-task pricing, and all data stays on your instance. Runs on Node.js with SQLite by default; add Postgres and Redis queue mode when you need to scale workers horizontally.

An entire backend in a single Go executable: PocketBase embeds SQLite with realtime subscriptions, authentication and user management, file storage, and an admin dashboard, all behind a REST-ish API. SQLite runs in WAL mode, which outperforms client-server databases for the read-heavy workloads typical of small and mid-sized apps. Authentication supports email/password, one-time passwords, and 15+ OAuth2 providers including Google, Apple, and GitHub, with stateless tokens. Clients subscribe to record changes over server-sent events, and official JavaScript and Dart SDKs cover web, mobile, and Flutter frontends. Collections, rules, and API access permissions are managed visually in the admin UI. When you need custom logic, extend it with JavaScript hooks running in the embedded JS VM of the prebuilt binary, or import PocketBase as a Go library and compile custom business logic into your own single-file backend. File storage attaches uploads to records with thumbnail generation for images and optional S3-compatible external storage. All state lives in one pb_data directory, so backup is a directory copy and upgrade is replacing a binary - one of the lowest-maintenance backends you can run. The contrast with Firebase is the point: where usage-based pricing scales with reads, writes, and bandwidth, PocketBase runs the entire backend at flat hosting cost, and the data is a plain SQLite file you can copy anywhere. MIT-licensed.

Seven million emails from a single binary peaking at 57 MB of RAM: listmonk is a high-performance newsletter and mailing list manager in Go with PostgreSQL as its only dependency - no Redis, no worker processes, no message broker. The project's own production benchmark sent 7+ million emails with the binary peaking around 57 MB of RAM, and throughput exceeds 100K emails per hour on modest hardware. Campaigns run through a multi-threaded, multi-SMTP queue with round-robin delivery, per-server concurrency, retries, and sliding-window rate limiting across providers like Amazon SES, SendGrid, Mailgun, or your own Postfix relay. Subscribers carry custom JSON attributes and are segmented with raw SQL queries, so any audience Postgres can express, listmonk can target. Templates use Go template syntax with 100+ functions for dynamic per-subscriber content, and the Vue dashboard reports opens, clicks, bounces, and unsubscribes with automated bounce processing. A REST API handles transactional email and programmatic control, a built-in media library hosts campaign assets, and CSV or API import migrates lists from hosted platforms. The economics are the headline: where Mailchimp pricing scales with list size, listmonk plus Amazon SES sends the same volume for hosting cost plus roughly $0.10 per thousand emails - commonly a 95% reduction - and your email list, a core business asset, stays on your own infrastructure. AGPLv3-licensed; bring your own SMTP provider for delivery.

An Airtable-style spreadsheet interface directly on PostgreSQL: Teable is an open-source no-code database where every table is a real Postgres table. Unlike tools that store records in a metadata abstraction layer, every Teable table is a real Postgres table with standard column types, so filtering, sorting, and grouping run at database speed, million-row tables answer complex filters in roughly 200 milliseconds without index tuning, and any PostgreSQL-compatible tool - psql, BI dashboards, ETL pipelines - can query the same data directly. The interface offers Grid, Kanban, Gallery, Calendar, and Form views as non-destructive overlays with their own filters and hidden fields, plus 20+ field types, formulas, comments, attachments, batch editing, undo/redo, and edit history. Collaboration is real-time with live cursors and instant sync across views, backed by Redis, and a REST API is auto-generated per table, largely compatible with Airtable API clients - alongside native SQL access for BI tools, analytics pipelines, and your own applications to JOIN and query directly, with no exports, API rate limits, or sync jobs. Global search spans all records, chart plugins handle quick visualization, and CSV and Excel import/export cover migrations. Where Airtable caps paid plans at 100K-500K rows and charges roughly $20 per user per month, a self-hosted Teable instance has neither limit: the Postgres database itself is the export if you ever leave. Built in TypeScript with NestJS, deployed via Docker with PostgreSQL and Redis, and licensed AGPL-3.0.

Prompt, run, edit, and deploy full-stack Node.js applications from a browser tab: Bolt.diy is the official open-source version of Bolt.new's AI coding agent. Its foundation is StackBlitz's WebContainer technology - a sandboxed in-browser Node.js environment where the AI controls the whole stack: filesystem, npm, dev servers, terminal, and browser console. That means the agent does not just generate code; it installs dependencies, runs Vite or Next.js, reads errors, and fixes them. The defining difference from Bolt.new is model choice per prompt: 19+ providers including OpenAI, Anthropic, Gemini, DeepSeek, Groq, Mistral, Amazon Bedrock, and local models via Ollama or LMStudio, extensible through the Vercel AI SDK. Development ergonomics include live preview, a diff view of AI changes, codebase search, file locking to prevent generation conflicts, 15+ starter templates (React, Vue, Next.js, Astro, Svelte, Expo), and MCP support for external tools. Projects integrate with Git and Supabase, and deploy in one click to Vercel, Netlify, or GitHub Pages.

Describe a component in natural language and watch it render: OpenUI, from Weights & Biases, is an open alternative to Vercel's v0. Type a prompt like "a dark-themed dashboard with a sidebar and charts" and the LLM renders working HTML with Tailwind styling live in the browser. You then iterate conversationally, asking for changes until the design is right, and convert the result to React, Svelte, or Web Components for use in a real project. The backend is Python with LiteLLM routing, so it works with OpenAI, Anthropic, Gemini, Groq, and Mistral API keys, or fully offline against local Ollama models, including vision models like LLaVA that can generate UI from screenshot input - feed a screenshot and the model reproduces or riffs on an existing interface. Generated markup is inspectable at any point, with light and dark mode toggles, theme selection, and responsive previews across device sizes. The practical effect is compressing the mockup-review-revise loop from hours to minutes: a described layout renders in seconds and iterates through follow-up prompts, and because output converts to real framework code, prototypes feed directly into production codebases instead of staying trapped in a design tool. Self-hosting keeps unreleased product interfaces and prompts on your own server, and LiteLLM routing lets you pick the model per task - a cheap fast model for rough drafts, a stronger one for final passes, or free local models for unlimited experimentation.

Your users belong in your own database - Authorizer, an open-source authentication and authorization server shipping as a single Go binary, keeps them there. It connects to 13+ backends - PostgreSQL, MySQL, SQLite, SQL Server, MariaDB, MongoDB, Cassandra, ScyllaDB, ArangoDB, DynamoDB, Couchbase, YugabyteDB, PlanetScale, and CockroachDB - so identity data lives beside the application it protects instead of in an auth vendor's cloud. The server is fully OAuth 2.0 and OpenID Connect compliant, including authorization code flow with PKCE, a JWKS endpoint, token revocation, and nine JWT signing algorithms. Login options cover email/password, magic links, TOTP multi-factor, SMS OTP via Twilio, and social providers including Google, GitHub, Apple, Microsoft, and Discord. Authorization goes beyond roles: an embedded OpenFGA engine provides Zanzibar-style relationship-based permission checks in process. APIs are exposed over GraphQL, REST, and gRPC, with SDKs for JavaScript, React, Go, and Python, plus themeable built-in login pages and an admin dashboard. Apache 2.0 licensed.

Salesforce's core workflow, open-source and on your own server: Twenty is a modern CRM built as exactly that alternative. It ships the standard CRM objects out of the box: people, companies, opportunities, notes, and tasks, displayed in table and kanban views with drag-and-drop and real-time updates. Its defining technical feature is a metadata-driven data model: you define custom objects and fields in the UI, and the backend regenerates its GraphQL schema at runtime, so a new object gets working queries, mutations, filters, and sorting within seconds, with no migrations to run - adapting the CRM to your sales process never requires code changes. A REST API is auto-generated from the same schema, GraphQL subscriptions push real-time updates, and webhooks fire on record changes for external integration. A visual workflow builder automates actions like notifications and field updates, TypeScript-based apps extend the platform with custom logic and frontend components, and email and calendar sync pulls Gmail messages and meetings onto contact timelines so communication history sits next to the record. The stack is NestJS with TypeORM, PostgreSQL, Redis, and BullMQ on the backend, React with Jotai on the frontend. Self-hosting on RepoCloud means unlimited users with no per-seat licensing - the pricing model that penalizes growing teams on commercial CRMs - and your pipeline, contacts, and deal history live in your own PostgreSQL database rather than a vendor's.

Drag nodes onto a canvas and ship an LLM app: Flowise is an open-source visual builder for AI agents and LLM applications, written in Node.js on LangChain.js and licensed Apache-2.0. You assemble flows by dragging nodes onto a canvas: models, prompts, memory, vector stores, retrievers, and tools, then wire them together and test in the built-in chat panel. Three builder types cover increasing complexity: Assistant for simple RAG chat over uploaded files, Chatflow for single-agent systems with techniques like rerankers and Graph RAG, and Agentflow for multi-agent orchestration with branching, looping, shared flow state, and human-in-the-loop checkpoints. Over 100 integrations connect data sources, vector databases, and both proprietary and open-source models, plus MCP client and server nodes for standard tool interop. Finished flows are exposed as REST APIs, embedded chat widgets, or via JS and Python SDKs - each flow gets an endpoint the moment it is saved, removing the deployment gap between a working prototype and something your application can call. Execution logs, visual step debugging, and external log streaming trace behavior, while input moderation and rate limiting act as guardrails; RBAC, SSO, and workspaces cover team deployments. Self-hosting keeps prompts, encrypted credentials, and conversation data on your own instance, which matters when flows handle internal documents or customer data - and wiring a model, prompt, memory, and vector store on the canvas replaces the boilerplate a hand-coded LangChain project would need.

In-app, website, link, and email surveys feed one open-source experience management platform: Formbricks. Its distinguishing strength is targeted in-app research: a JavaScript SDK triggers surveys on user events and attributes, with segmentation rules like "power users who have not seen a survey in 10 days," so questions reach the right cohort at the right moment instead of a mass email blast. The no-code editor offers 20+ question types including NPS, CSAT, CES, matrix, ranking, and file upload, with skip logic, conditional branching, best-practice templates, and full brand theming. Responses feed built-in analytics with summaries and CSV/JSON export, and integrations push data to Slack, Notion, Google Sheets, Airtable, Zapier, and n8n, with webhooks and an open API on every tier. Because self-hosted surveys load from your own domain rather than a blacklisted third-party script host, ad blockers do not suppress them - in-app surveys reach users that Hotjar-style tools silently miss, which measurably raises response rates. Self-hosting also removes the third-party sub-processor from your privacy policy entirely: survey responses often contain PII, and keeping them on your own server matters for GDPR-sensitive and regulated industries. The Community Edition has no response caps or tier-gated features, so core functionality and your data stay accessible regardless of any subscription. Next.js on PostgreSQL, AGPLv3.

Retool's job, self-hosted: ToolJet is an open-source low-code platform for building internal tools, dashboards, and admin panels. Apps are assembled in a drag-and-drop visual builder with 60+ responsive components, including tables, charts, forms, and lists, and connected to 80+ data sources: PostgreSQL, MySQL, MongoDB, REST and GraphQL APIs, cloud storage, and common SaaS tools. When visual configuration is not enough, you can run JavaScript or Python inline for queries and transformations. A built-in no-code database (ToolJet Database) covers apps that need their own tables without provisioning an external database, Workflows add node-based automation for background jobs with dedicated worker containers and a Redis-backed queue, and multi-page apps with multiplayer editing, inline comments, and mentions support team development. Security is designed for internal data: credentials are AES-256-GCM encrypted, data flows proxy-only through your server so database contents never reach a third-party cloud, and granular per-app access control plus SSO gate each tool. Where Retool-style platforms bill per builder and sometimes per end user, the self-hosted Community Edition serves unlimited builders and users at hosting cost, and full source availability means the platform itself can be forked, audited, and extended. The stack is Node.js and React on PostgreSQL, deployed via Docker.

Admin panels, database GUIs, dashboards, approval flows, customer support consoles - Appsmith builds the internal tools your team keeps postponing, on an open-source low-code platform. The UI assembles from 45+ drag-and-drop widgets - tables with server-side pagination and inline editing, charts, forms, lists, buttons - which bind to data through {{ }} JavaScript expressions anywhere in the editor. Datasources cover PostgreSQL, MySQL, MongoDB, MS SQL, Redis, Snowflake, and more, plus any REST or GraphQL API, with SaaS integrations and AI query support for prompt-based steps inside apps. When the widget library falls short, custom widgets are plain JavaScript, HTML, and CSS, and external JS libraries can be imported, which keeps the platform extensible where pure no-code tools hit walls. Git-based version control enables branch-based collaboration, review, and rollback of app definitions. Queries and JS objects hold the business logic layer between datasources and UI. Self-hosted via Docker or Kubernetes, with role-based access control for published apps.

Large language models get a polished front end that can run fully offline: Open WebUI is the self-hosted front end of choice. It talks to local model runners, primarily Ollama, and to any OpenAI-compatible API, so LM Studio, vLLM, Groq, Mistral, OpenRouter, and cloud providers all plug into the same chat interface and can be mixed per conversation. RAG is built in: upload files to knowledge bases or reference them in chat with the # command, backed by a choice of nine vector databases (ChromaDB and PGVector officially maintained) and multiple extraction engines including Tika and Docling, with hybrid BM25-plus-vector search and cross-encoder reranking. Web search results from providers like SearXNG, Brave, and Tavily inject directly into conversations. Extensibility comes from Python tools and functions that run inside the chat, a Pipelines plugin framework, and native MCP support. Multi-user features include RBAC, SSO, and group permissions, and the instance itself exposes an OpenAI-compatible API your own apps can call.

A private ChatGPT built with Next.js: Lobe Chat is the open-source AI chat interface teams self-host instead. Its main advantage is provider breadth: one interface connects to 40+ model providers, including OpenAI, Anthropic Claude, Google Gemini, Mistral, Groq, AWS Bedrock, Azure, and local models served through Ollama, so you can switch models per conversation and compare outputs. It handles multi-modal work: image recognition, image generation, text-to-speech, and speech-to-text. A plugin system based on function calling and the Model Context Protocol (MCP) adds external tools like web search and code execution. Run it in standalone mode as a single container with settings in browser storage, or in database mode with PostgreSQL and S3-compatible storage for persistent history, multi-user auth, and RAG knowledge bases built from uploaded documents with pgvector retrieval. Because tools arrive through function calling and MCP rather than a proprietary plugin format, custom internal tools can be exposed to the assistant with a standard server over STDIO or HTTP. Hundreds of pre-configured assistant roles import from the community marketplace. For teams the cost model matters: provider API keys billed per token typically undercut a ChatGPT Plus seat per person, and self-hosting keeps API keys, uploaded files, embeddings, and conversation history entirely on your own server.

Airtable's spreadsheet-database model, self-hostable and open-source: that is Baserow. It presents data in a spreadsheet-style grid, but underneath each table is a real relational structure with typed fields, links between tables, filters, sorts, and multiple views (grid, gallery, form, kanban, calendar). Beyond the database core, it includes an application builder for composing pages and portals on your data, workflow automations, and dashboards. Everything is API-first: each table exposes a REST endpoint with token auth and webhooks, so it plugs directly into n8n, Zapier, or custom scripts. The stack is Django (Python) on the backend, Vue.js on the frontend, PostgreSQL for storage, with Redis for async tasks. Core features are MIT-licensed; premium features are a paid add-on. The self-hosted version has no row, storage, or API request limits - Airtable's per-base record caps and monthly API quotas simply don't exist here, and capacity is bounded only by your PostgreSQL database and disk. Existing Airtable bases, CSVs, and Excel files import directly with structure preserved, so migration doesn't start from a blank slate, and both the backend and frontend support plugins for custom field types and integrations without forking the core. For non-technical teammates the interface behaves like a spreadsheet; for engineers, the data model is the API.

Prototype multi-agent AI systems without writing orchestration code: AutoGen Studio is Microsoft's low-code interface over the AutoGen AgentChat framework. You compose teams of LLM-powered agents in a visual Team Builder, either by drag-and-drop from a component library or by editing the declarative JSON specification directly. Each agent gets a model, a prompt, tools (Python functions), and the team gets termination conditions and an orchestration pattern, sequential or LLM-driven. The Playground runs teams interactively with live message streaming between agents, a visual control-transition graph, tool-call and code-execution tracking, and pause/stop controls, which makes it a practical debugger for agent behavior. Finished teams export as JSON for use in any Python application via the TeamManager class, or serve as an API endpoint. Any OpenAI-compatible model endpoint works, including local servers like Ollama or vLLM. Microsoft labels it a research prototype: use it for prototyping and evaluation, and build production systems on the underlying AutoGen framework.

Your own Heroku or Vercel on a single server - Dokploy is the open-source, self-hosted Platform-as-a-Service that makes the swap. You point it at a Git repository or a Docker image, and it builds and deploys the application using Dockerfiles, Nixpacks, or Heroku/Paketo buildpacks. Traefik is integrated as the reverse proxy, handling routing, load balancing, automatic Let's Encrypt SSL certificates, and HTTP/3. It also provisions and manages databases (MySQL, PostgreSQL, MongoDB, MariaDB, Redis) with automated backups to external storage. Complex multi-service applications deploy through native Docker Compose support, and multi-node scaling uses Docker Swarm. The web UI covers environment variables, volumes, resource limits, real-time CPU/memory/network monitoring, and deployment logs, with a CLI and API for automation. Deployment notifications go to Slack, Discord, Telegram, or email. One-click templates install common open-source tools, and a single Dokploy control plane can manage deployments across multiple remote servers. Because everything is standard Docker under the hood, there is no lock-in: your Dockerfiles, Compose files, and data volumes work anywhere else Docker runs. You get the Heroku-style push-to-deploy workflow without operating a Kubernetes cluster, and the total cost is the server it runs on - no per-app, per-environment, or per-seat platform fees regardless of how many applications you deploy.

Zapier's job, on your own server: Activepieces is an open-source workflow automation platform built to be exactly that replacement. Flows are built in a visual no-code editor with triggers, actions, loops, conditional branches, auto-retries, raw HTTP steps, and code steps that run JavaScript or TypeScript with full npm package support. Integrations are "pieces" - type-safe TypeScript npm packages with hot reloading for local development - and the catalog spans 600+ services, with the large majority contributed by the community. The platform is AI-first in two directions: native AI pieces call OpenAI, Anthropic, Google, and Azure models inside flows, and every piece automatically doubles as an MCP server, so assistants like Claude Desktop and Cursor can invoke your integrations and workflows through natural language. A built-in MCP server also exposes 30 tools for building flows, managing tables, and running tests agentically. Flows are fully versioned with draft and locked states. The core is MIT-licensed and runs on TypeScript with PostgreSQL and Redis.