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.

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.

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.

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.

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.

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.

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.

Marketing campaigns and transactional mail from one open-source platform: Notifuse is a modern, self-hosted alternative to Mailchimp, Brevo, and Klaviyo without per-email or per-contact pricing. Built with Go and React on PostgreSQL, it separates concerns cleanly: a drag-and-drop visual builder composes responsive templates from MJML components with Liquid variables like {{ contact.first_name }} and per-template version history; campaigns add A/B testing across subject lines, content, and send times; and a REST transactional API serves application-triggered mail. Delivery routes through your choice of provider - Amazon SES, Mailgun, Postmark, SendGrid, SparkPost, Mailjet, or plain SMTP - with multi-provider failover. Contacts carry custom fields and a full activity timeline (messages, profile changes, webhook events), and real-time segmentation builds dynamic rules over properties, activity, and subscriptions. Event-driven automations create behavioral sequences, a notification center gives recipients self-service preference management, and an S3-compatible file manager handles images with CDN delivery. Multi-tenant workspaces with isolated databases and custom domains suit agencies. Open and click tracking report engagement in real time.

Build, deploy, and monitor chatbots and LLM-powered agents on one open-source conversational AI platform: Botpress. Its Studio is a visual development environment: a drag-and-drop canvas arranges conversation logic with nodes for messages, questions, choices, and actions, while a built-in emulator simulates conversations for debugging before anything goes live. Agents ground their answers in a knowledge base assembled from uploaded documents, ingested websites, and past conversations via retrieval-augmented generation, and the LLM layer connects to multiple model providers - GPT-4, Claude, Mistral - with a configurable model strategy. An autonomous engine handles reasoning, tool orchestration, persistent memory across sessions, and sandboxed code execution, and custom code actions in TypeScript extend agents past prebuilt workflows. Over 100 integrations deploy the same bot to WhatsApp, Telegram, Slack, Microsoft Teams, and web chat, and connect it to HubSpot, Zendesk, Zapier, and arbitrary APIs and webhooks. Human handoff, conversation analytics, and quality monitoring cover production operation. Originating in 2017 from a Montreal team, the community edition is developed openly on GitHub.

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.

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.

Contracts signed on your own server: DocuSeal is the most feature-complete open-source, self-hosted alternative to DocuSign. A WYSIWYG builder turns any PDF into a fillable form with 14 field types: signature, initials, date, file upload, checkbox, dropdown, radio, stamp, and more. Documents route to multiple submitters in sequence or parallel, with automated SMTP email notifications, reminders, and a mobile-optimized signing experience that works on any device without an account. Every completed document carries an automatic PDF eSignature with verification and an audit trail. Templates are reusable and can also be generated programmatically - from HTML via API or from PDFs and DOCX files with embedded field tags - and the REST API plus webhooks drive full workflow automation, with embedded signing forms and form builders for React, Vue, Angular, and plain JavaScript. Files store on disk or in S3, Google Cloud Storage, or Azure. The UI ships in 7 languages with signing in 14. Runs on SQLite, PostgreSQL, or MySQL; AGPL-3.0 licensed with unlimited documents and no per-signature fees.

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.

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.

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.

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.

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.