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.

Agents with tool use, deep research, a document editor, an IMAP/SMTP email client with AI triage, notes, tasks, and a CalDAV-synced calendar - Odysseus bundles all of it into one open-source, self-hosted AI workspace. It runs local models through Ollama, vLLM, or llama.cpp and cloud APIs like OpenAI and OpenRouter, with a hardware-aware Cookbook that scans your machine and recommends quantized models that fit. Persistent memory uses ChromaDB with hybrid vector-plus-keyword retrieval, web search runs through a bundled SearXNG instance, and agents can use MCP servers, files, and shell access with safety controls, plus custom skills and scheduled agent tasks. A blind Compare mode runs side-by-side model duels with identities hidden and accumulates Elo-style ratings from your votes, so model selection is based on your actual workloads rather than leaderboard claims. Deep research mode - adapted from the Tongyi DeepResearch approach - reads sources through SearXNG and produces cited reports, while the email client tags, summarizes, sets reminders, and drafts replies locally rather than through a third-party mail AI. The writing-first document editor adds AI edits, Markdown and HTML support, and version history. The stack is Python 3.11 with FastAPI, SQLite for state, and a vanilla JS frontend, licensed AGPL-3.0 with zero telemetry. Because agents can read email and execute commands, keep authentication enabled and never expose it as a public unauthenticated service.

The most widely deployed open-source BI tool, Metabase is a visualization and query layer that sits on top of your existing databases without ingesting or copying data. Non-technical users ask questions through a visual query builder with drill-through menus that answer follow-ups like "broken down by month" without writing a new query, while analysts use the native SQL editor with variables and templates for complex work. Questions assemble into interactive dashboards with filters, auto-refresh, fullscreen mode, and custom click behavior, and dashboard subscriptions email or Slack scheduled reports to stakeholders. It connects to 20+ data sources including PostgreSQL, MySQL, MongoDB, SQL Server, BigQuery, Snowflake, Redshift, and ClickHouse - always querying in place, so there is no second data store to secure, sync, or pay for, and results are always current. Models and metrics let a data team define official, reusable starting points so self-service stays consistent, collections with permissions organize content, and alerts fire when a metric crosses a threshold. The practical effect is cutting the ad-hoc query queue that lands on the data team, since non-technical staff can answer their own questions. Written in Clojure, licensed AGPL, and shipped as a single JAR or Docker image with an embedded application database - a working BI instance runs before most tools finish their installer - the open-source edition has no limits on users, dashboards, or connected databases, where commercial BI platforms price per viewer as well as per creator.

The integrations your SaaS product offers its own users - that is what Nango, an open-source product-integrations platform, exists to build. It solves the repetitive infrastructure work behind every third-party API connection: OAuth flows, API key handling, token refresh, encrypted credential storage, rate-limit backoff, retries, and multi-tenant connection management. It ships pre-built auth configurations for 800+ APIs. Your users connect their accounts through an embeddable, white-label Connect UI, and your backend then reads or writes data through Nango's proxy, SDKs, or REST API without ever touching raw credentials. Integration logic is written as TypeScript functions covering actions, scheduled data syncs, and webhook processing - all running on one runtime with retries, checkpointing, and per-connection logs built in. Syncs pull records incrementally on a schedule, one-way or two-way, which suits RAG pipelines, search indexing, and keeping local copies of external data current. Selected actions can also be exposed as tool schemas or through a built-in MCP server, so AI agents operate on user-connected accounts without ever handling provider credentials. Auth support spans OAuth 2.0, OAuth 1.0a, API keys, basic auth, and JWT, and observability - logs, metrics, failure detection, and a reconnect flow for expired credentials - is scoped per customer connection for easier support debugging. Works with any backend language. Self-hosting on RepoCloud keeps all customer credentials and synced data on infrastructure you control, which matters for data residency and compliance requirements.

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.

Roughly $1M of development work, open-sourced: Maybe Finance began as a $249/year commercial personal finance product before the company released it all. It aggregates bank accounts, credit cards, loans, investments, crypto, and real estate into a single net worth dashboard with historical trend charts - replacing the spreadsheet that usually glues a whole portfolio together. Transactions are categorized and tagged with rules, with merchant tracking and search across imported or synced activity; budgets track spending by category against plan; and the investment view follows holdings, cost basis, and returns across brokerage accounts. Multi-currency support converts accounts held in different currencies into a single reporting currency, bank synchronization works through Plaid where supported, and manual CSV import covers any institution. An optional AI assistant answers questions grounded in your own financial data. Because the app was built as a paid product with professional design before being open-sourced, its interface quality exceeds most community finance tools - and self-hosting means your balances and transactions are not monetized by a free app or gated behind an annual subscription. The stack is Ruby on Rails with Hotwire on PostgreSQL, licensed AGPL-3.0 and deployed via Docker. The original repository is archived; development continues in the community fork Sure, compatible with the same self-hosted setup.

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.

Roughly 40 integrated business apps forming a full ERP: Odoo's open-source suite runs companies end to end. The Community Edition, licensed LGPL-3.0, ships roughly 40 apps covering CRM, sales, invoicing, basic accounting (journals, chart of accounts, taxes, reconciliation), inventory and warehouse management with multi-step routes, manufacturing with BOMs and work orders, purchasing, project management, timesheets, HR, a website builder, and eCommerce. Each app works standalone, but they share one PostgreSQL database and one data model, so a confirmed sale updates stock, triggers procurement, and posts invoices without integration glue. The modular design means you enable only the apps you need and extend with 40,000+ community modules from the Odoo app store covering nearly any vertical requirement. Inventory supports multi-warehouse stock, reordering rules, and lot and serial tracking with barcode-ready operations; manufacturing ties BOMs, work orders, and work-center routing directly to sales demand and stock levels; and the website builder sells straight from your product catalog with payment provider integrations. You can start with just CRM and invoicing on day one and switch on inventory or eCommerce later - new apps integrate with existing data instantly because the schema is shared. The server is Python with an XML/JavaScript view layer, and because data lives in plain PostgreSQL there is no proprietary format: you can query, back up, migrate, and extend business data directly, with unlimited users and no per-seat licensing - where enterprise ERP pricing is per user per month, headcount here costs nothing.

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.

Open the page, write a Markdown note, move on - Memos is a lightweight, self-hosted service built for quick capture. Instead of folders, notebooks, and titles, it presents a timeline: open the page, write a Markdown note, and move on. Notes support headings, code blocks with syntax highlighting, task lists, tables, and file attachments, with tags auto-extracted from #hashtags in the text. Each memo carries a visibility level, private, protected (logged-in users), or public, so one instance works as a personal log, a small team wiki, or a lightweight microblog. The backend is a single Go binary with a React frontend, around 50 MB of memory at runtime and a ~20 MB Docker image, so it fits comfortably on the smallest instance size with near-zero maintenance. SQLite is the default store, with MySQL and PostgreSQL supported for multi-user deployments needing more concurrency, and full REST and gRPC APIs - Connect RPC for browsers, gRPC-Gateway for external tools - make capture scriptable from CLIs, bots, and automation platforms. Fast full-text search spans all memos, pinned notes keep references handy, and a masonry view suits visual browsing. MIT-licensed with zero telemetry; content is stored as plain Markdown in a database you control, so notes remain readable, exportable, and free of proprietary formats.

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.

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.

Sketch a wireframe, get working code: Draw a UI turns hand-drawn layouts into web interfaces. It pairs the open-source tldraw canvas with an OpenAI vision model: you sketch a layout - boxes, labels, buttons, arrows, whatever communicates the idea - select the drawing, and click Make Real. The app snapshots your selection as a PNG, sends it to the vision API with instructions to return a single HTML file styled with Tailwind CSS, and renders the result in an iframe directly on the canvas next to your sketch. The loop is iterative: annotate the generated prototype or redraw parts of it, select both the sketch and the previous result, and generate again - the model receives the earlier HTML as context and produces an updated version. Built by Figma engineer Sawyer Hood as one of the first viral GPT-4 Vision demos and the basis for tldraw's "Make Real", it is a Next.js app that runs against your own OpenAI API key. Self-hosting matters here: the upstream demo ships without authentication, so a private deployment keeps your API key from being drained by strangers. MIT-licensed.

Typeform's conversational format, self-hosted: HeyForm is the open-source form builder that presents one question at a time. Forms present one question at a time, which measurably improves completion rates compared to long static pages. It supports 40+ field types, from text, email, and phone inputs to picture choices, date pickers, star ratings, signatures, and file uploads. Conditional logic shows or hides questions based on earlier answers, routes respondents to different endings, and redirects to URLs, so a single form can serve multiple flows. Completed submissions land in a results dashboard with drop-off and completion analytics, and connect outward through webhooks or integrations with Zapier, Make, Google Sheets, Notion, Airtable, and Slack. Theming covers fonts, colors, backgrounds, and custom CSS, so embedded forms look native to your site rather than like a third-party widget; the JavaScript embed library renders them inline, as popups, or full-page, with shareable standalone links as the default. Team workspaces and projects with member management let multiple teams share one instance without mixing data. Self-hosting removes per-response pricing entirely - unlimited forms and submissions for flat hosting cost - and keeps lead data, feedback, and quiz answers in your own MongoDB, simplifying GDPR compliance. The stack is a NestJS server and React webapp backed by MongoDB and KeyDB, distributed under GPLv3 as a Docker image.

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.

Thirteen-plus LLM providers, one unified client: NextChat (formerly ChatGPT-Next-Web) is an open-source AI chat interface built on Next.js that spans OpenAI GPT-4, Anthropic Claude, Google Gemini, DeepSeek, Groq, Azure endpoints, and self-hosted backends like Ollama, LocalAI, and RWKV-Runner. Its defining trait is minimalism - the first screen loads in about 100 KB, the desktop client is roughly 5 MB, and there is no database or user system to operate; chat history lives locally in the browser with optional WebDAV or UpStash Redis sync. The Mask system saves reusable prompt-template personas you can share and debug, long conversations auto-compress to fit context windows, and Markdown rendering covers LaTeX, Mermaid diagrams, and code highlighting with streaming responses. Plugins add web search and calculators, MCP support enables external tool calling, and Artifacts previews generated content in a separate pane. Ships as a web app, Docker image, and Tauri desktop builds for Windows, macOS, and Linux, translated into 20+ languages. MIT-licensed.

Automatisch runs your Zapier workflows on your own hardware - an open-source, self-hosted automation platform built as a direct alternative. Flows are chains of steps: one trigger (a polling or webhook event such as a new GitHub issue, a Stripe payment, or a form submission) followed by action steps that pass data downstream (post to Slack, append a Google Sheets row, update Notion). The visual builder deliberately mirrors Zapier's trigger-action model, so migrating existing Zaps requires no retraining and no programming knowledge. Roughly 60 integrations cover common business services - Slack, GitHub, Google Sheets, Notion, Stripe, Discord - and connections store credentials per service, with multiple accounts per app supported. Every execution runs on your own server: execution history, logs, and payload data never touch a third-party processor, which matters for GDPR, healthcare, and finance workloads. Error handling with retry logic, a REST API for programmatic flow management, and Docker Compose deployment round out the platform. The AGPL-3.0 Community Edition has no feature limits or per-task billing; an Enterprise Edition adds SSO, roles, and audit logs.

Website analytics, uptime monitoring, and server status - three tools most teams run separately - combined in Tianji, an open-source observability platform. The analytics layer tracks page views, unique visitors, referrers, and UTM parameters with a lightweight cookie-less script, which keeps collection GDPR and CCPA friendly. The uptime monitor checks availability and latency on configurable intervals, accepts passively reported results, and publishes public status pages for incident communication. Server status agents report CPU, memory, disk, and network metrics with threshold-based alerts, and notifications route through webhooks, Slack, Telegram, and other channels with noise control. It also includes anonymous telemetry for tracking deployments of your own open-source projects, surveys, waitlists, team collaboration, and an OpenAPI interface for integrations and exports. The consolidation is the point: traffic analytics, uptime checks, and server metrics share one interface and one alerting layer, so diagnosing an incident does not mean hopping between Google Analytics, Uptime Kuma, and Prometheus - and the built-in public status pages replace a separate paid Statuspage-style subscription. Because collection uses no cookies with IP truncation and aggregation by default, basic traffic measurement requires no consent banner. Built in TypeScript under the Apache 2.0 license and inspired by Umami and Uptime Kuma, it is deliberately right-sized for independent developers and small SaaS teams whose monitoring needs are real but lightweight.