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.

Merge, split, compress, convert, edit, annotate, redact, OCR, and sign PDFs - BentoPDF packs over 130 tools into a privacy-first toolkit that runs entirely in the browser through WebAssembly. Files are never uploaded - processing happens in browser memory on the user's machine and disappears when the tab closes, which makes the tool GDPR-clean by architecture and safe for financial, legal, and internal documents. The engine combines WASM builds of PyMuPDF, Ghostscript, and CoherentPDF; Tesseract handles OCR with searchable text-layer output; Office conversions cover Word, Excel, and PowerPoint; and digital signatures use X.509 certificates (PFX/PEM) with the private key staying on the client. Because there is no server-side processing, deployment is a static-file exercise: a single Docker container, or any static host. A dedicated self-hosted build strips the marketing pages while keeping every tool, and air-gapped deployments are first-class - an automated script bundles the WASM modules, OCR language data, and fonts for fully offline networks. No accounts, no limits, no watermarks; TypeScript and Vite under the hood.

Every major model provider behind one ChatGPT-style interface: LibreChat spans OpenAI, Anthropic, Google, Azure, AWS Bedrock, Vertex AI, Groq, Mistral, OpenRouter, DeepSeek, and any OpenAI-compatible endpoint including local Ollama. You can switch models mid-conversation and compare providers without changing tools. Its Agents framework builds no-code custom assistants with tool access via Model Context Protocol servers, file search over uploaded documents through an optional pgvector-backed RAG service, and a sandboxed Code Interpreter that executes Python, JavaScript, Go, C++, Java, PHP, and Rust. Artifacts render React components, HTML, and Mermaid diagrams directly in chat, and image generation works through DALL-E and other configured providers. Multi-user support is enterprise-grade, with OAuth, SAML, LDAP, and two-factor authentication, per-user conversation history in MongoDB, and Meilisearch-powered search across all messages and files, plus reusable presets, forkable threads, and persistent memory across conversations. The economics favor teams: instead of a ChatGPT Plus seat per person, everyone shares one instance billed per API token, with access to every provider rather than one - and providers see individual API calls, not your accumulated organizational knowledge. Deployment is Docker Compose; API keys and endpoints are configured through .env and librechat.yaml.

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.

The open-source PaaS with 55,000+ GitHub stars and the largest one-click service catalog in its class — Coolify gives you the Vercel push-to-deploy workflow on a dedicated server you control. Connect a GitHub, GitLab, Bitbucket, or Gitea repository and every push builds and deploys automatically via Nixpacks, a Dockerfile, or Docker Compose, with Traefik or Caddy reverse proxying, automatic Let's Encrypt certificates, and per-branch preview deployments with their own URLs. Databases — PostgreSQL, MySQL, MariaDB, MongoDB, Redis — provision in a few clicks, and a catalog of 280+ one-click service templates covers WordPress, n8n, Grafana, MinIO, Plausible, Ollama, and more. One dashboard manages the entire server, with Docker Swarm available for clustering multiple nodes. Backups go to any S3-compatible storage with one-click restore, and a full API supports CI/CD integration. All configuration lives on your own server, so resources keep running even if you stop using Coolify — no vendor lock-in by design. Running on a dedicated VPS with guaranteed CPU, RAM, and SSD, full root access via SSH and browser console. Apache 2.0 licensed.

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.

Teams that cannot send messages through someone else's cloud run Mattermost - the open-core, self-hosted alternative to Slack. It provides public and private channels, threaded discussions, unlimited search history, file sharing with previews, one-to-one audio calls, and screen sharing, with desktop clients for Windows, macOS, and Linux plus iOS and Android apps. Messages support full Markdown, which suits engineering conversations with code blocks and logs. Playbooks turn repeatable processes such as incident response and release management into checklist-driven workflows with automated triggers and retrospectives. Integration is a core strength: prebuilt connectors for GitHub, GitLab, Jira, ServiceNow, and PagerDuty, plus webhooks, slash commands, bots, a REST API, and a plugin marketplace with 700+ entries - together making it a working surface for ChatOps rather than just a chat room. Playbooks add keyword and event triggers, task assignment, status broadcasting, and post-incident retrospectives, so operational knowledge is not trapped in individuals' heads. The server is a single Go binary backed by PostgreSQL, with React clients, released monthly under MIT license and deployable fully air-gapped - which is why governments and defense organizations run it inside closed networks, and why the same control applies to any team with confidentiality requirements. The compiled Team Edition is free for unlimited users with no message history cutoff, so costs stay flat as the team grows.

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.

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.

A personal AI assistant that remembers what it learns and reaches you wherever you are — OpenClaw is an open-source agent gateway built by the OpenClaw Foundation with 247,000+ GitHub stars. It connects to 200+ LLM models through providers like Anthropic, OpenRouter, and OpenAI, and meets you on 21+ messaging channels: Telegram, Slack, Discord, WhatsApp, Signal, iMessage, Matrix, and more. Persistent memory with full-text search lets the agent recall context across sessions, and a self-improving skills system means it gets more capable the longer it runs. Voice wake words and talk mode enable hands-free interaction on macOS, iOS, and Android. A live canvas provides an agent-driven visual workspace. Built-in browser automation, cron scheduling for unattended tasks, and subagent spawning for parallel workstreams round out the toolset. The gateway architecture keeps all sessions, credentials, and conversation history on your own server — nothing transits a third-party cloud unless you choose to connect one. The API key you provide for your chosen LLM provider powers the underlying calls; billing goes through your own account. Running on a dedicated VPS with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

CRMs, project trackers, inventory tools - NocoBase is an open-source no-code/low-code platform for building business systems like these. Its architecture is data-model driven: you define collections and relationships first, then compose any number of interface blocks (tables, forms, kanban, charts) on top of the same model, so data structure is never coupled to a particular view. The core is a microkernel where every feature is a plugin, WordPress-style; you enable official plugins, install marketplace ones, or write your own as npm packages with server and client parts. Data sources include the main PostgreSQL or MySQL database, external databases, and third-party APIs - so you can build admin panels over existing production data instead of migrating it. Built-in infrastructure covers role-based permissions down to collection, record, and field level, workflow automation with approval steps and scheduled triggers, and audit logs; a one-click switch flips between usage and configuration modes. Because custom features live in isolated plugins with a documented lifecycle, core upgrades do not overwrite your customizations, and swapping UIs never requires data migrations since interfaces sit on independent models. Written in TypeScript on Node.js, Koa, and React under the AGPL license, it is light enough for one person to run and extend - and where no-code SaaS platforms charge per seat and per app, a self-hosted instance runs unlimited applications for unlimited users at hosting cost alone.

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.

Chat with your own documents: AnythingLLM, from Mintplex Labs, wraps retrieval-augmented generation (RAG) in an open-source application anyone can run. You organize content into workspaces, each an isolated namespace with its own documents, vector embeddings, chat history, and settings, so one instance can hold several separate knowledge bases. Upload PDFs, DOCX, TXT, and other formats, or scrape web pages; the built-in collector parses and chunks them into a vector database (LanceDB by default, with Pinecone, Chroma, Qdrant, and others supported). Answers cite their source documents. It works with both cloud LLMs (OpenAI, Anthropic, Gemini) and local ones via Ollama or LM Studio, and the embedding model is separately configurable. Beyond RAG chat, it includes AI agents that can browse the web and run tools, an embeddable chat widget for your website, a developer API, and multi-user mode with admin, manager, and default roles plus per-workspace access control. Context assembly is smarter than naive RAG: pinned documents, attached files, vector search hits, and recent chat history are combined under a token budget so the model's context window is filled efficiently, and each workspace supports multiple independent conversation threads against the same knowledge base. Because the embedding model, vector store, and chat LLM are all independently swappable, you can move between providers without re-ingesting a single document. The stack is Node.js with a React frontend, MIT-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.

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.

Perplexity's search experience without Perplexity: Vane deploys Perplexica, an open-source AI answer engine built as the self-hosted alternative. Instead of returning a page of links, it reads your question, searches the live web through the SearxNG metasearch engine, and composes a direct answer with cited sources. Retrieval quality comes from embeddings and similarity search: fetched pages are re-ranked against the query so the model answers from the most relevant passages rather than whatever ranked first. Two query modes cover different needs - Normal mode runs a straightforward web search, while Copilot mode generates multiple reformulated queries and actively pulls content from top matches for harder questions. Focus modes specialize retrieval for academic papers, YouTube, Reddit discussions, Wolfram Alpha calculations, or the general web. The answering model is your choice: OpenAI-compatible APIs or fully local LLMs such as Llama 3 and Mixtral through Ollama, which keeps queries entirely on your infrastructure. Because SearxNG pulls live results, answers reflect current information, and no search history is tracked.

Quote to cash in one web application - create quotes, convert them to invoices, record payments, track customers: iDURAR is an open-source ERP and CRM platform for small and medium-sized businesses. Built on the MERN stack (MongoDB, Express, React, Node.js) with Ant Design components and Redux state management, it presents a clean SaaS-style interface that needs little onboarding. Core modules cover invoice management with PDF generation and email delivery, payment recording against invoices, quote and proforma handling, customer records, and accounting views over the resulting data. Multi-currency support and localization make it usable for internationally operating teams. Because the whole stack is JavaScript with an API-first backend, extending it - custom fields, new modules, integrations - is approachable for any Node/React developer rather than requiring a specialist ERP skill set. Deployment is straightforward via Docker with a MongoDB instance. Licensed under AGPL-3.0 with free commercial use; a hosted enterprise version exists but the self-hosted edition is fully functional.

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.