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.

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.

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.

A self-hosted "second brain": Khoj indexes your own files and answers questions from them, parsing Markdown (whole Obsidian vaults included), org-mode, PDF, Word, plain text, Notion pages, GitHub repositories, and images described by a vision model, then embedding everything with sentence-transformers into a vector index for semantic search and RAG with cited sources. Any LLM backend works: local models like Llama, Qwen, or Mistral via Ollama, or cloud models like GPT, Claude, and Gemini. You can build custom agents, each with its own persona, scoped knowledge base, chat model, and tools such as web search and code execution. Scheduled automations run recurring research and deliver newsletters or notifications to your inbox, and research mode performs multi-hop web searches with inline citations. Access it from a browser, the Obsidian plugin, Emacs, desktop, or WhatsApp - all clients connect to the same self-hosted instance, making Khoj one of the few AI assistants Emacs users can point at decades of org files. Semantic search means recall works without exact keywords: "that paper about forecasting with transformers" surfaces the right PDF even when you cannot remember its title. Switching LLM backends never requires re-indexing your documents, and with a local model via Ollama, even inference stays on hardware you control - journals, research, and private notes are never sent anywhere. Python/FastAPI stack, AGPL-licensed, with PostgreSQL storage.

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.

Data, AI, and infrastructure workflows, orchestrated from declarative YAML: Kestra is an open-source, event-driven orchestration platform. Flows are declared in YAML - no DSL rewrites or Python decorators - and the definition stays the single source of truth even when edited through the UI, API, CI/CD, or Terraform, which makes pull-request review, versioning, and rollback natural. Tasks run in any language: Python, Node.js, Go, Rust, R, SQL, or Bash scripts executed in containers, and a plugin ecosystem of 1,000+ integrations covers ingestion, dbt, Airbyte, Spark, cloud storage, databases, and messaging systems. Scheduling supports cron triggers, event triggers, backfills, and conditional branching, with retries, timeouts, error handling, and typed inputs and outputs that surface artifacts in the UI. Namespaces, labels, and subflows organize workflows at scale, and the embedded code editor includes Git integration. Common uses span ETL/ELT pipelines, dbt runs, microservice coordination, infrastructure provisioning, and human-in-the-loop approvals. Java-based, Apache 2.0 licensed, deployed via Docker or Kubernetes.

Any SSH-accessible Linux box - VPS, bare metal, Raspberry Pi, EC2 - becomes a Heroku-like deployment environment under Coolify, an open-source, self-hostable platform-as-a-service. Connect a GitHub, GitLab, Bitbucket, or Gitea repository and every push builds and deploys automatically via Nixpacks, a Dockerfile, or Docker Compose, with Traefik 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, and more, replacing an afternoon of Compose YAML with a two-minute operation. One dashboard manages multiple servers, with Docker Swarm available for clustering. Backups go to any S3-compatible storage with one-click restore, a browser terminal gives real-time server access, and a full API supports CI/CD integration. All configuration lives on your own servers, so resources keep running even without Coolify. Apache 2.0 licensed.

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.

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.

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.

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.

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.

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.

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.

The de facto dashboard of observability: Grafana is the open-source frontend that turns the data stores you already run into interactive graphs. It does not store metrics itself; it connects to the data stores you already run and turns their contents into interactive dashboards. Supported sources number over 150 via plugins: Prometheus, Loki, Tempo, InfluxDB, Elasticsearch, MySQL, PostgreSQL, Microsoft SQL Server, AWS CloudWatch, Azure Monitor, Google Cloud Monitoring, and many more. Dashboards are built from a large library of panel types (time series, heatmaps, tables, gauges, logs) with template variables for reusable, parameterized views. Unified alerting evaluates rules against any connected data source, not just Prometheus, and routes notifications to Slack, PagerDuty, email, and other channels with grouping and silencing - unlike Prometheus Alertmanager, a single rule can combine a Loki log pattern, a PostgreSQL query result, and a CloudWatch metric. Dashboards serialize to JSON and data sources configure via provisioning files, so the entire observability setup can live in Git and deploy repeatably across environments. Explore mode adds ad-hoc querying outside dashboards, with split view for correlating a metric spike against the matching log lines, and access control spans organizations, teams, folder permissions, and OAuth, LDAP, and SAML integration. Written in Go and TypeScript, AGPL-licensed. Self-hosting gives you unlimited users, dashboards, and queries at flat hosting cost, without Grafana Cloud's usage-based pricing.

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.

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.