Open Source App Cloud Marketplace

Add a series once, set a quality profile, and everything downstream is automated: Sonarr is the smart PVR for Usenet and BitTorrent users. It monitors RSS feeds from your indexers, detects new episodes the moment they release, sends matching grabs to SABnzbd, NZBGet, qBittorrent, Deluge, or another download client, then renames files with fully configurable templates, sorts them into consistent folder structures, and notifies Plex, Kodi, or Jellyfin to update the library. Quality profiles define what's acceptable (HDTV, WEB-DL, Blu-ray, up to 4K) and an upgrade cutoff - when a better release appears, Sonarr replaces the existing file automatically, stepping from HDTV to WEB-DL to Blu-ray until the cutoff is met. Custom formats add weighted scoring for finer-grained release selection, with community-maintained TRaSH Guides presets as the widely accepted defaults. Failed downloads are handled without intervention: Sonarr retries with another release, and manual search shows every candidate with the reasons any was rejected. It scans existing libraries for missing episodes, fully supports specials, multi-episode files, and daily and anime series types, and a calendar view shows upcoming episodes across every tracked show. Runs on Linux, Windows, macOS, and Raspberry Pi, and pairs naturally with Prowlarr for centralized indexer management.

Built to consolidate fragmented digital life into a private personal cloud, Eclaire centralizes tasks, notes, documents, photos, and web bookmarks into a unified workspace powered by local artificial intelligence. Users can save web articles to generate clean Markdown copies and searchable PDF archives, automatically bypassing clutter and dead links. The integrated document ingestion engine extracts tabular data from spreadsheets, performs optical character recognition across uploaded receipts and handwritten images, and indexes multi-page PDF manuals for rapid full-text search. Conversational assistant panels allow operators to interrogate their accumulated library using natural language, asking for cross-document summaries, research timelines, or action items extracted from meeting transcripts. Background workers prioritize asynchronous indexing queues, categorizing image libraries with visual object tags and managing recurring task deadlines with automated Telegram alert notifications. External automation flows can interact directly with the unified storage layer via an OpenAI-compatible REST API, allowing mobile shortcuts and custom scripts to ingest bookmarks and dictate notes remotely. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

Images, text, audio, video, HTML, PDFs, and time series, labeled in one tool with a standardized output format: Label Studio is the open-source data labeling platform for building training datasets. Computer vision tasks cover classification, object detection (boxes, polygons, ellipses, keypoints), and semantic segmentation; audio work spans transcription, speaker diarization, and emotion recognition; NLP handles named entity recognition and document classification with taxonomies up to 10,000 classes; and GenAI workflows support LLM fine-tuning data and RLHF response ranking. Labeling interfaces are fully configurable with an XML-like templating language, so the UI matches the task instead of the reverse. The ML backend SDK turns any model into a connected web server for pre-annotation (model predicts, humans verify), interactive labeling (real-time predictions as annotators draw regions or highlight text), and model evaluation - cutting annotation time dramatically on large datasets. Data imports from S3, GCS, or file uploads; the Data Manager filters and explores tasks; exports convert to the format your ML library expects via label-studio-converter. Multi-user accounts tie every annotation to its author, and webhooks, a Python SDK, and REST API embed labeling into any pipeline. Self-hosting keeps proprietary training data - often a company's most sensitive asset - entirely on your infrastructure.

Kokoro-FastAPI turns text into natural-sounding speech across eight languages by serving the 82-million-parameter Kokoro-82M model through an OpenAI-compatible REST API, so any existing OpenAI SDK client can generate audio by just changing the base URL. With over 5,300 GitHub stars since December 2024, the fully Dockerized FastAPI server covers American English, British English, Spanish, French, Hindi, Italian, Japanese, Brazilian Portuguese, and Mandarin Chinese with language-specific phoneme processing. Inline voice mixing blends multiple profiles using weighted ratios like af_bella(2)+af_heart(1), automatically normalizing weights and caching combined voicepacks as PyTorch tensor files for reuse. Audio streams in real time over HTTP with configurable chunk sizes, or generates complete files in MP3, WAV, OPUS, FLAC, AAC, or PCM formats with speed control from 0.25x to 4.0x. Per-word timestamped captions with speaker-tagged voice labels enable subtitle generation for podcasts, audiobooks, and accessibility workflows. Pre-built Docker images support NVIDIA GPU acceleration via CUDA, experimental AMD GPU inference via ROCm, and CPU-only deployment on linux/amd64 and linux/arm64 architectures, with Apple Silicon MPS support available through direct UV execution. The integrated web interface at port 8880 provides browser-based speech generation, while the Swagger UI at /docs exposes the full API reference. Debug endpoints report system statistics for monitoring inference load. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. Apache 2.0 licensed.

Trusted by millions of engineers and deployed on over 80,000 GitHub stars worth of community confidence, Netdata delivers true real-time monitoring at per-second granularity — 10-60x faster than Prometheus, Datadog, or any conventional monitoring stack that averages away the transient anomalies lasting 2-10 seconds where most production incidents originate. A single installation command deploys the agent with zero configuration, automatically discovering every running process, container, systemd service, network connection, disk, and application on the host within seconds. Unsupervised machine learning trains multiple models per metric directly at the edge, detecting anomalies without thresholds, baselines, or manual tuning. The distributed Parent-Child architecture scales horizontally from a single Raspberry Pi to fleets exceeding 100,000 nodes while maintaining sub-2-second visualization latency and storing metrics at approximately 0.5 bytes per sample through tiered compression. Native network monitoring provides live topology maps, NetFlow and sFlow analytics, SNMP device polling across 200+ profiles, and trap handling — capabilities that typically require a separate NPM product. Hundreds of pre-configured alerts cover systems and applications out of the box, with AI-powered root cause analysis surfacing correlated metrics through natural language via MCP-compatible AI assistants. The agent supports Linux, macOS, FreeBSD, Kubernetes, and Docker with eBPF-based kernel observability requiring no application instrumentation. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. GPL v3+ licensed.

Positioned as the open-source NotebookLM alternative for AI agents, SurfSense delivers a live web research platform where your agents access structured data from Reddit, YouTube, Instagram, TikTok, Amazon, Walmart, Google Maps, Google Search, Indeed, and any page on the open web through one REST API or MCP server. Scheduled and event-triggered agents transform findings into briefs, alerts, podcasts, and presentations, while a built-in knowledge base keeps every discovery searchable with Perplexity-style cited answers using hybrid semantic and full-text search powered by PostgreSQL with pgvector. Upload PDFs, Office documents, images, and audio files, or sync Google Drive, OneDrive, and Dropbox — 50+ file formats supported with AI file sorting that auto-organizes documents by source, date, and topic. The MCP server exposes scrapers, knowledge base, and workspaces as native tools for Claude, Cursor, and any MCP-compatible agent. Cross-country proxy rotation handles Reddit, TikTok, and Google Search scraping with geo-aware sticky sessions and captcha-aware anti-bot handling. The platform features collaborative chats, multi-format document export, git-native knowledge base with Open Knowledge Format export, and a desktop quick-ask panel with global shortcut. Docker Compose deployment manages nine services including Caddy proxy, PostgreSQL, Redis, FastAPI backend, Celery workers, zero-cache real-time sync, and Next.js frontend with automatic Watchtower updates. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. AGPL-3.0 licensed.

Magento's extensibility without PHP, Shopify's polish without the platform tax: EverShop is the TypeScript-first e-commerce platform built on that promise. Architected as a modular monolith on Node.js, it organizes every piece of business logic - catalog, checkout, customers, your custom extensions - into modules that plug in without touching core code, extended through a disciplined set of mechanisms: registry processors for transforming data across modules, hooks that wrap function calls, async event subscribers (product created, order placed), and route middleware. The storefront and the fully-featured admin panel are both React with server-side rendering and hydration, giving fast first paint and SEO-friendly pages, while a typed GraphQL API (plus REST endpoints) serves exactly the data each view needs - the same API that powers headless and PWA builds. Standard commerce is covered: product management with variants and attributes, category navigation, cart and checkout, order and customer management, coupons, and a theme system built on React components and Tailwind for deep storefront customization. PostgreSQL is the default database, deployment is Docker-friendly with near-zero configuration, and the GPL-3.0 license means the entire stack - types, resolvers, and checkout flow included - is yours to read and modify.

With over 45,000 GitHub stars and 100 million Docker pulls, Milvus is the most widely adopted open-source vector database, powering production AI systems at NVIDIA, Salesforce, eBay, Airbnb, and DoorDash. The distributed architecture separates compute and storage with stateless microservices on Kubernetes, horizontally scaling query nodes for read-heavy workloads and data nodes for write-heavy ingestion independently. Milvus 3.0 introduces lake-native retrieval that builds and serves indexes directly over vector data in object storage and open formats including Parquet, Lance, Iceberg, and Vortex without maintaining separate copies. Native hybrid search unifies lexical BM25 full-text retrieval and semantic vector search in a single engine with metadata filtering, eliminating the need for separate search infrastructure. Hardware-accelerated ANN indexing supports IVF, HNSW, DiskANN, and GPU-based indexes with BitQ 1-bit quantization cutting memory usage by 72 percent. SDKs for Python, Go, Node.js, and Java provide programmatic access, while Milvus Lite offers lightweight embedding for local development via pip install. Server-side aggregation, sorting, faceted search, StructArray for nested document structures, and ColBERT multi-vector scoring move ranking and result processing into the engine. The Path Index enables 100x faster JSON filtering with support for 100,000+ collections per cluster for multi-tenant deployments. Self-hosting deploys via Docker Standalone or Kubernetes with Helm charts using S3-compatible, GCS, or Azure Blob storage backends. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. Apache 2.0 licensed.

AzuraCast is a solution for running internet radio stations, packaging the entire broadcast stack into a single Docker installation that gets you on air in minutes. Built on PHP with a Vue.js frontend, it uses Liquidsoap as the AutoDJ engine to compile media from playlists, live DJ inputs, and scheduled programming into composited output streams, then broadcasts via Icecast-KH, SHOUTcast 2 DNAS, or Rocket Streaming Audio Server to thousands of concurrent listeners. The media library supports drag-and-drop uploads with automatic metadata extraction, while playlist management handles sequential, random, weighted, and time-scheduled rotations. Live DJ accounts let remote broadcasters connect via BUTT, Mixxx, or any Icecast-compatible software, with automatic crossfade transitions between AutoDJ and live input. The built-in Web DJ tool enables broadcasting directly from the browser without additional software. Each station includes public-facing player pages with now-playing metadata, album art, song history, and embeddable widgets for external websites. The listener request system lets audiences queue songs through the public interface. Multi-station administration hosts unlimited stations on a single server with individual user accounts and granular role-based permissions. Comprehensive analytics track listener counts, geographic distribution, unique listeners, and listening duration with exportable reports. HLS streaming delivers adaptive bitrate broadcasts for mobile compatibility. LADSPA audio plugins enable professional equalization and processing in the stream pipeline. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. AGPL-3.0 licensed.

GCHQ open-sourced its "Cyber Swiss Army Knife", and CyberChef became the web app security analysts, incident responders, and CTF players reach for when data needs decoding, decrypting, or dissecting. Its interface is four panes: paste or drag input (files up to 2GB), search a categorized library of hundreds of operations, drag them into a recipe with arguments, and read the output. Operations span Base64, hex, and XOR encoding; AES, DES, and Blowfish encryption; classical ciphers from Caesar to Railfence; hashes and checksums; compression; regex and string extraction of IPs, domains, and URLs; timestamp conversion; and parsers for IPv6, X.509 certificates, and more. Recipes chain arbitrarily - convert from a hexdump then decompress, decrypt AES pulling the IV from the cipher stream, or let the Magic operation auto-detect several layers of nested encoding. Auto Bake re-runs the recipe live as input or arguments change, Step executes one operation at a time for debugging, and flow control (forks, subsections, registers) applies different operations to different parts of the data. Recipes save to files or share as URLs encoding the full pipeline. Crucially, CyberChef is entirely client-side JavaScript - nothing uploads anywhere - and self-hosting guarantees an unmodified copy inside your own network, where malware artifacts belong.

Created by Uber Technologies and graduated as the seventh CNCF top-level project in October 2019 with over 23,000 GitHub stars, Jaeger has become one of the most widely deployed open-source distributed tracing platforms, processing billions of spans per day in production environments at organizations including Uber, Red Hat, and Shopify. Version 2 rebuilt the platform on the OpenTelemetry Collector framework, inheriting its extensible pipeline architecture while implementing Jaeger-specific features as extensions and components, enabling seamless integration with the OpenTelemetry ecosystem through native OTLP protocol support. The platform stores traces in Cassandra 4.0+, Elasticsearch 7.x/8.x, OpenSearch 1.0+, ClickHouse, or the embedded Badger database for development setups. Three sampling strategies control trace volume: head-based sampling with constant, probabilistic, and rate-limiting modes, tail-based sampling using the OpenTelemetry Collector processor that evaluates complete traces before storage decisions, and adaptive sampling that dynamically adjusts probabilities based on observed traffic patterns. Service Performance Monitoring computes RED metrics directly from spans, displaying request rates, error rates, and latency percentiles in the Monitor tab with drill-down from aggregate service views to individual traces. The web UI provides trace search with multi-field filtering, trace detail views with span timeline visualization, trace comparison across services, and dependency graphs mapping service relationships from actual traffic. Deployment options range from a single all-in-one binary for development to distributed collector-ingester-query configurations with Kafka intermediate buffering for production scale. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. Apache 2.0 licensed.

With over 9,100 GitHub stars and production deployments powering real-time analytics at companies like SHOPLINE where it reduced API latency by 76.7%, RisingWave is the PostgreSQL-compatible streaming database that collapses the traditional Debezium-plus-Kafka-plus-Flink-plus-serving-database stack into a single Rust-powered system. The platform continuously ingests data from PostgreSQL and MySQL via native CDC connectors that eliminate Debezium middleware, consumes Kafka, Redpanda, Pulsar, and Kinesis topics, accepts webhook events from SaaS applications, and batch-loads historical data from S3 and data warehouses. Standard SQL defines sources, materialized views, and sinks — no new DSL, no Java, and no custom API — while the PostgreSQL wire protocol means psql, DBeaver, pgAdmin, Grafana, Metabase, Superset, Tableau, and every PostgreSQL client library works without modification. Materialized views are incrementally maintained as events arrive, delivering point lookups in single-digit milliseconds without recomputing aggregates from scratch. For long-term retention, RisingWave writes to Apache Iceberg tables with a hosted REST catalog and automated table maintenance including compaction, small-file optimization, and snapshot cleanup, with data queryable by Spark, Trino, DuckDB, and DataFusion. The disaggregated compute-storage architecture uses S3-based state management for elastic scaling, instant failure recovery measured in seconds rather than the minutes-to-hours typical of RocksDB-based systems, and cost-efficient storage tiering. An MCP server enables AI agents to query and operate RisingWave directly. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. Apache 2.0 licensed.

Meteroid delivers the billing infrastructure that SaaS companies need when Stripe Billing gets too rigid and building in-house gets too expensive. The Rust backend ingests usage events via REST API or Kafka with deduplication by event ID and customer ID, storing time-series data in ClickHouse for sub-second aggregation queries across billions of events. Billable metrics transform raw events — API calls, compute time, tokens, storage, transactions — into accurate charges using configurable aggregation functions, dimensions, and filters without pre-aggregation. The plan builder supports any pricing structure: flat rate, per-unit, tiered graduated, tiered volume, package, and hybrid combinations with multiple price components per plan. Versioned plans enable pricing changes without affecting existing subscribers through grandfathering, while experiments let you A/B test pricing with controlled rollouts. Subscription management handles the full lifecycle — creation, upgrades, downgrades, mid-cycle proration, scheduled changes, and cancellation with configurable grace periods. The TypeScript frontend provides a complete web dashboard for managing customers, plans, subscriptions, invoices, and revenue analytics with MRR tracking, churn analysis, and cohort insights. Automated invoice generation handles complex scenarios including usage-based line items, credits, discounts, and tax calculations with PDF rendering. Stripe Connect integration enables payment collection directly through the platform. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. AGPL-3.0 licensed.

The deep end of self-hosted recipe management: Tandoor Recipes is a Django/Vue application that replaces Paprika, AnyList, and ad-choked recipe sites with a database you control. Import is where most people start: paste any URL and Tandoor scrapes schema.org markup for ingredients, instructions, images, times, and nutrition; bulk-paste URLs for batch import; or migrate wholesale from Mealie, Paprika, Nextcloud Cookbook, Pepperplate, and other managers with built-in importers. The structured recipe editor tracks ingredients individually, which is what powers everything downstream: full-text search with trigram similarity, a "what can I make with what's in the fridge" ingredient search, automatic nutrition via OpenFoodFacts, and shopping lists that merge duplicate ingredients across recipes, convert units, scale by servings, and sort by your supermarket's actual aisle layout. The weekly meal planner is drag-and-drop, feeds shopping lists automatically, exports to your calendar, and shows a nutritional summary for the week. Multi-user support comes with a granular permission system - shared household cookbooks, private recipes, even secret ones - and shopping lists sync in real time so two people can shop simultaneously. A full REST API integrates with Home Assistant and Grocy. For households serious about cooking, Tandoor's depth is unmatched.

Perplexity's answer-engine experience, self-hostable and open-source: Morphic searches the web and writes cited answers. Instead of returning a list of links, it searches the web, reads the sources, and generates a complete answer with inline numbered citations. The generative UI streams rich components, source cards with thumbnails, image grids, syntax-highlighted code, and LaTeX math, rather than plain markdown. Quick mode answers fast; Adaptive mode runs deeper multi-step research. Search backends are pluggable: the Docker Compose bundle ships with a private SearXNG instance so no search API key is required, and Tavily, Brave, and Exa are supported alternatives. LLM providers include OpenAI, Anthropic, Google, Ollama, and any OpenAI-compatible endpoint, with per-mode model mapping - fast, cheap models for quick searches, stronger models for adaptive research, tuning the cost-quality trade-off per query type. An inspector panel exposes tool execution during multi-step research, and AI-suggested follow-up questions keep an investigation moving. Chat history persists in PostgreSQL, results are shareable by URL, file uploads feed context into queries, and optional Supabase authentication adds multi-user or guest access. Because the default search path is your private SearXNG instance, research topics never hit a commercial search API - and with local Ollama models the marginal cost of a query approaches zero. Built with Next.js, TypeScript, and the Vercel AI SDK under Apache 2.0.

With 32,800 GitHub stars, 180 contributors, and version 3.2 shipping in July 2026, SurrealDB eliminates the database zoo by unifying document, graph, relational, time-series, geospatial, and key-value data models into a single Rust binary queried through SurrealQL — an intuitive SQL-like language that handles graph traversals, record links, subqueries, and computed fields without switching between multiple database engines. Purpose-built for AI applications, it integrates vector indexing, full-text search, and hybrid retrieval that blends semantic similarity with graph and relational intelligence for context-aware RAG pipelines and recommendation engines. Real-time subscriptions and event-driven triggers push live data changes to connected clients without requiring external message brokers like Kafka. Multi-row, multi-table ACID transactions guarantee consistency while incrementally computed views deliver pre-calculated analytics without batch processing. Role-based access control with record-level permissions, JWT authentication, and multi-tenant isolation enables backend-as-a-service usage where client applications connect directly with fine-grained security. SDKs for JavaScript, Python, Go, Rust, .NET, and Java connect via WebSocket or HTTP APIs. Storage and compute separation allows deployment as an embedded library, a single-node server, or a highly-scalable distributed cluster with TiKV or FoundationDB backends. Deploy via Docker with persistent volumes on any Linux host. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. Source-available licensed.

Build a voice AI agent that answers calls, qualifies leads, books appointments, and transfers to a human when needed, all from a drag-and-drop workflow builder in your browser. Dograh ships as a Docker Compose stack (API, web UI, Postgres, Redis, MinIO) that you self-host on any Linux server with automatic HTTPS provisioning via Let's Encrypt. The visual workflow builder lets you design multi-turn conversation flows by connecting nodes for greetings, intent classification, tool calls, and handoffs; describe your use case in plain English and the platform generates the LLM prompt and node graph for you. Connect your own speech-to-text, LLM, and text-to-speech providers (OpenAI, Anthropic, Gemini, ElevenLabs, Deepgram, local Whisper, Kokoro, or any OpenAI-compatible endpoint) or use the built-in Speech-to-Speech mode with Gemini Flash Live and GPT-Realtime-2 for sub-200ms latency. Telephony plugs in through Twilio, Vonage, Vobiz, or Cloudonix for inbound and outbound calling, with live agent transfer when the conversation needs a human. Webhook tool calls connect to Salesforce, HubSpot, Google Calendar, Cal.com, or any REST API without writing orchestration code. The ClonedVoice feature mixes real human voice recordings for high-frequency phrases with neural TTS fallback for dynamic content, cutting costs while improving caller trust. A built-in MCP server lets AI coding agents like Claude Code or Cursor design, test, and edit workflows through natural language. Deploy on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. BSD 2-Clause licensed.

Pi Web is a browser interface for the Pi coding agent ecosystem, providing a visual workspace that reads the same local configuration and session files as the CLI. The session workspace groups conversations by project with running state indicators, context usage percentages, cost tracking, and compaction details, while two branching modes let users create independent session files from earlier messages or fork branches within existing sessions to explore alternative coding directions. Real-time streaming via Server-Sent Events delivers agent responses with structured Markdown rendering, thinking steps, tool call visualization, and image drag-and-drop input. The project file explorer browses working directories with syntax-highlighted source preview, Git diff inspection, and rendering for Markdown, images, audio, PDFs, and DOCX files with automatic refresh. Git worktree support switches checkouts from the sidebar while keeping sessions from the same repository grouped together. The Models panel manages provider authentication via OAuth and API keys, model selection, model smoke tests, and models.json configuration shared bidirectionally with the CLI agent. The Skills panel lists, searches, installs, and toggles agent skills without terminal access. The interface ships with English and Simplified Chinese translations, light and dark themes, a chat minimap, keyboard shortcuts, and completion sounds. Basic Auth protects remote access when binding to non-loopback addresses. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.