Plunk consolidates transactional emails, marketing campaigns, and drip automation into one platform riding AWS SES at roughly one-tenth of a cent per message, with zero per-contact charges regardless of list size. The Turborepo monorepo architecture separates the Express.js API server (handling REST requests with Prisma ORM against PostgreSQL) from a dedicated BullMQ worker process that consumes email, campaign, and workflow jobs independently for fault isolation and horizontal scaling. Transactional emails support HTML bodies, template variable substitution via React Email components, attachments, and custom headers with dedicated SMTP relay on ports 465 and 587 for integration with existing frameworks. The campaign system sends newsletters and product updates to full contact lists or dynamically segmented audiences based on contact properties and behavioral events, with scheduling, A/B testing, and performance tracking for opens, clicks, and bounces. The workflow automation builder creates event-triggered sequences with delays, conditional branches, and webhook steps for lifecycle campaigns like onboarding drip sequences and re-engagement flows. Contact management stores unlimited contacts with custom data fields, CSV import, full activity history, and dynamic segmentation. Custom domain verification with DKIM and SPF ensures deliverability, while inbound email processing handles incoming messages with custom routing rules. Docker Compose deployment runs five containers including PostgreSQL, Redis, MinIO for S3-compatible storage, and ntfy for notifications. 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.

With over 3,700 GitHub stars and growing adoption among teams tired of managing complex orchestration platforms, Dagu delivers a complete workflow engine as a single Go binary that requires no external database, message broker, or framework installation. Define directed acyclic graphs in declarative YAML — specifying dependencies, schedules, retries, timeouts, approvals, and notifications — while keeping existing shell scripts, containers, and tools completely unchanged. The built-in Web UI provides live pipeline visualization, per-step log streaming, run history browsing, artifact previewing, manual retry controls, and workflow YAML editing without SSHing into servers. Execute steps as shell commands, Docker containers, Kubernetes Jobs, SSH remote commands, SQL queries, or HTTP requests, with conditional branching and parallel execution handled natively. The integrated Model Context Protocol server exposes dagu_read, dagu_change, and dagu_execute tools, enabling AI agents like Claude, Codex, and Cursor to inspect workflow state, preview YAML modifications, and control runs through authenticated endpoints. The harness.run executor lets external coding-agent CLIs operate inside DAG steps with full scheduling and approval gate support. Scale beyond a single machine with the distributed worker mode, which dispatches tasks to remote nodes via gRPC with automatic label-based routing and worker selection. Deploy with Docker, the official Helm chart for Kubernetes, or a simple binary download requiring only a Linux, macOS, or Windows host. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. GPLv3 licensed.

Prototype multi-agent AI systems without writing orchestration code: AutoGen Studio is Microsoft's low-code interface over the AutoGen AgentChat framework. You compose teams of LLM-powered agents in a visual Team Builder, either by drag-and-drop from a component library or by editing the declarative JSON specification directly. Each agent gets a model, a prompt, tools (Python functions), and the team gets termination conditions and an orchestration pattern, sequential or LLM-driven. The Playground runs teams interactively with live message streaming between agents, a visual control-transition graph, tool-call and code-execution tracking, and pause/stop controls, which makes it a practical debugger for agent behavior. Finished teams export as JSON for use in any Python application via the TeamManager class, or serve as an API endpoint. Any OpenAI-compatible model endpoint works, including local servers like Ollama or vLLM. Microsoft labels it a research prototype: use it for prototyping and evaluation, and build production systems on the underlying AutoGen framework.

Deploying container updates without blind surprises is what Drydock delivers through a monitor-first inspection plane that evaluates image registries, scans CVE vulnerabilities, and automates rollbacks across distributed Docker infrastructure. Systems engineers track container fleets across twenty-three public and private registries including Docker Hub, GitHub Container Registry, Harbor, and Quay using cursor-based pagination and semver classification. The integrated Update Bouncer runs Trivy and Grype static scanners against incoming candidate layers, blocking deployments that fail configurable CVE severity policies while verifying cryptographic signatures through cosign. Operators configure declarative update schedules with stabilization countdown gates that hold back brand-new releases until defined burn-in periods elapse. When updates execute, Drydock creates pre-upgrade container snapshots and evaluates post-launch container health checks, instantly restoring previous image digests and network configs if failures occur. Distributed Portwing edge agents stream live container output and system logs over encrypted WebSockets, allowing central consoles to coordinate remote daemon updates without opening inbound host firewall ports. Automated event triggers dispatch granular notifications and update payloads across seventeen communication channels including Slack, Discord, Telegram, and Home Assistant MQTT brokers. 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.

Backed by Y Combinator and powering scraping infrastructure across 195 countries, Anakin delivers a production-grade web scraping API purpose-built for AI agents and RAG pipelines that need clean, structured data from sites that actively block conventional scrapers. The single Go binary server handles JavaScript-heavy SPAs through its Camoufox anti-detect browser service with automatic fingerprint rotation, while the HTTP-first handler chain tries lightweight extraction before escalating to full browser rendering — keeping response times under 2 seconds for static pages. The built-in React 19 dashboard provides visual scraping with live results, job tracking with status filters, domain configuration management with handler chain CRUD, and proxy performance monitoring via Thompson Sampling scoring. Structured JSON extraction leverages Gemini AI to transform raw HTML into typed schemas without manual selector maintenance. SDKs span Python, TypeScript, Go, .NET, Java, and Ruby, while the MCP server exposes all 21 tools directly to Claude, Cursor, Windsurf, and any Model Context Protocol-compatible agent. The hosted platform extends the open-source engine with AI web search returning full page content with citations, multi-source agentic research across 20+ sources per query, Wire pre-built actions covering 944 websites with 5,201 structured endpoints, persistent browser sessions for authenticated scraping, and website change monitoring with scheduled alerts. Deploy via Docker Compose with three containers or run the binary directly with optional PostgreSQL persistence. 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.

Kandev provides a command center for orchestrating AI coding agents across parallel workstreams. The Go backend paired with a Next.js frontend delivers kanban boards with drag-and-drop columns, pipeline workflow definitions with per-step agent handoffs, and an IDE-like review workspace combining file editor, file tree, terminal, browser preview, and unified git diffs. Multi-provider support connects Claude Code, GitHub Copilot, Codex, Qoder, Grok, and custom agents through configurable profiles with per-agent prompts, runtimes, and review gates. Tasks execute in isolated git worktrees with multi-repository support, letting agents work on separate branches simultaneously while changes surface in a consolidated review interface. Native integrations with GitHub, GitLab, Jira, Linear, Sentry, and Slack pull external issues into the kanban and link tasks to pull requests. Kandev exposes streamable HTTP and SSE MCP endpoints, enabling external clients — Cursor, Claude Desktop, Augment — to create tasks and read workspace context programmatically. Workflow definitions export as portable YAML for sharing across installations. Agentic workflows chain multi-step pipelines mixing different models per step — Opus for architecture, Sonnet for implementation, with human review gates between stages. 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.

Databasement puts scheduled backup and restore for nine database engines behind one polished web interface, deployed as a single Docker container on port 2226. The Laravel and Livewire backend uses native CLI tools for MySQL 5.6 through 9.x, PostgreSQL 12 through 18, MariaDB 10.x through 12.x, Microsoft SQL Server 2017 through Azure SQL, MongoDB 4.2 through 8.0, SQLite 3.x, Firebird 3.x through 5.x, Redis 2.8+, and Valkey 7.2+ with full restore support including cross-server recovery. SSH tunnel connectivity reaches databases behind firewalls via bastion servers with password or private key authentication, and remote agents handle isolated networks by connecting outbound over HTTPS without inbound ports. Scheduling supports arbitrary cron expressions with GFS grandfather-father-son retention alongside simple time-based cleanup. Storage spans local disk, S3-compatible services including AWS and MinIO, Azure Blob, Samba/SMB shares, and SFTP/FTP servers. Scheduled restores automate production-to-staging synchronization on recurring intervals. Failure notifications alert via Email, Slack, Discord, Telegram, Pushover, Gotify, and webhooks with detailed job logs. The REST API and built-in MCP server enable CI/CD pipeline integration and AI assistant access from Claude, Cursor, and VS Code Copilot. 1,700+ stars since November 2025. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

Configuring recurring cron jobs via version-controlled YAML manifests becomes seamless with GoCron, giving systems engineers and DevOps administrators a responsive web console to orchestrate scheduled commands with hot-reloading and sandboxed execution. Administrators can declare schedules using standard five-field cron syntax, establish global default configurations, and inherit execution timeouts, retry policies, and environment variable expansions across individual tasks. The interactive web interface provides immediate visibility into upcoming runs, past execution durations, status badges, and expandable terminal output logs stored in local SQLite databases. Operators can trigger ad-hoc job runs on demand, cancel stalled processes, and utilize a built-in sandboxed terminal utility governed by strict command whitelists. Automated health check webhooks dispatch HTTP notifications to external monitoring services upon job initiation, successful completion, or unexpected execution failure. The container environment bundles common server utilities including Restic, BorgBackup, and Rclone, streamlining automated offsite database backups and cloud storage synchronization routines without additional dependencies. Dynamic configuration reloading automatically detects filesystem modifications to YAML manifests without restarting the daemon, ensuring zero-downtime schedule updates. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

Automate transactional and marketing messages across email, SMS, mobile push, WhatsApp, Slack, and custom webhooks from a single visual journey canvas. Dittofeed provides the capabilities of Customer.io or Braze while keeping customer PII within your own infrastructure and eliminating volume-based pricing entirely. The drag-and-drop journey builder creates multi-trigger automations with branching logic, wait nodes, random cohort splits for A/B testing, and local timezone delivery without writing code. User segments combine trait conditions, event history, and array-based filtering through AND/OR operators with real-time evaluation. Template authoring supports both a low-code visual editor and direct HTML/MJML input, with templates reusable across journeys and one-off broadcasts. Data flows in through Segment integration, Reverse ETL connections, or the REST API with Web, Node.js, and React Native SDKs. Message delivery routes through SendGrid, Amazon SES, Twilio, or SignalWire with per-channel analytics tracking opens, clicks, bounces, and unsubscribes. Authentication supports Keycloak, AWS Cognito, and GCP OAuth for enterprise SSO. Embeddable iframe and headless React components let SaaS platforms white-label journey builders into their own products. Deploy on RepoCloud with a dedicated VPS for full GDPR compliance under the MIT license.

Agentic SOC Platform compresses hours of manual security analysis into seconds by deploying specialized AI agents that autonomously triage, investigate, and enrich security alerts. The Python/Django backend processes SIEM webhooks through Redis Streams into a modular pipeline where LangGraph-orchestrated agents extract IOCs, correlate signals, and generate Cases with severity, confidence, impact, priority, and structured verdicts. The built-in SIRP provides full case management with Alerts, Artifacts, Enrichments, Tickets, and a Knowledge base that accumulates institutional memory for both human analysts and LLM agents. Native Splunk and Elasticsearch/Kibana integrations deliver unified log search through a standardized interface so agents and analysts share identical security context. The playbook engine combines traditional SOAR automation with AI-powered investigation — launching threat hunting agents, knowledge extraction, threat intelligence enrichment, and CMDB lookups from a single orchestration layer. MCP Plugin support exposes ASP capabilities to Claude Code, Codex, and OpenCode, enabling external AI agents to operate cases, search logs, query threat intelligence, and write custom modules directly. Python Modules adapt new alert sources while Playbooks orchestrate LLM analysis and automated response actions, scaling the platform with your security scenarios. Deploy via Docker Compose with all data staying inside your network. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

Meet your new digital sidekick, the Fully Autonomous AI Agent! This isn't just any AI; it's like having a superhero in your terminal, browser, and editor. Ready to tackle complex tasks and projects with a single command, this AI Agent is your go-to for making tech magic happen. And with RepoCloud, you're not just saving on costs, you're also joining a league of extraordinary users harnessing the power of open-source collaboration. Get ready to elevate your productivity to legendary levels!

With 2,400+ GitHub stars, HolyClaude replaces a two-hour manual setup process with a single docker compose up command that launches a fully configured AI coding workstation. The container ships with Claude Code pre-installed alongside seven additional AI CLIs — Gemini CLI, OpenAI Codex, Cursor, TaskMaster AI, Junie, OpenCode with OpenRouter multi-provider support, and Pi Coding Agent — all accessible through the CloudCLI browser-based web interface on port 3001. A headless Chromium browser running on Xvfb display :99 comes pre-configured with Playwright 1.61 for automated screenshots, testing, and web scraping without additional setup. The development toolchain includes Node.js 26, Python 3, TypeScript, git, GitHub CLI, database clients for PostgreSQL, SQLite, and Redis, plus deployment CLIs for Vercel, Wrangler, Netlify, and Azure. Process management uses s6-overlay for automatic restarts and graceful shutdown, while bind mounts to ./data/claude and ./workspace ensure credentials, configuration, and project files persist across container rebuilds. The full image supports AMD64 and ARM64 architectures, running on Linux, macOS with Docker Desktop, Windows with WSL2, and Synology or QNAP NAS hardware. A slim tag at roughly 2GB omits the browser stack for environments that do not need it, while the full image at 4GB includes everything. Users authenticate with their existing Anthropic account directly through Claude Code with no credential relay or proxy involved. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

Salesforce's platform model, 100% open-source (Apache 2.0): Corteza is a Go/Vue.js low-code platform developed under a foundation, so there is no open-core bait to grow out of. The heart is Corteza Compose: namespaces contain applications, modules define record structures the way Salesforce objects do, and a drag-and-drop page builder assembles record pages, list pages, dashboards, and charts from configurable blocks. Automation comes from a visual, BPMN-style workflow engine plus JavaScript automation scripts, so cross-application business logic - approval chains, field updates, notifications - is configured rather than programmed. Granular role-based permissions reach down to individual modules, fields, and records, mirroring real organizational hierarchies. Corteza CRM ships as the flagship application built entirely on Compose: leads, accounts, opportunities, campaigns, and cases with a 360-degree customer view, covering most Salesforce standard objects - and because it is just a Compose app, adding or reshaping modules is configuration, not a fork. Everything is reachable over REST APIs, deliberately familiar tooling eases Salesforce admin migration, and a CLI can even generate synthetic records for load-testing what you build.

Listening to music across Spotify on your commute, Jellyfin at your desk, and Sonos in the living room usually leaves your play history fragmented across walled gardens, which is why multi-scrobbler unifies over 30 music sources and routes every track to your chosen scrobble backends automatically. Instead of relying on brittle browser plugins per device, you configure active polling or ingress webhooks once for sources including Plex, Navidrome, Subsonic, Apple Music, Deezer, YouTube Music, MPD, VLC, Chromecast, and Music Assistant. Every detected play passes through an intelligent pipeline that verifies listen duration thresholds, cleans messy track titles or featured artist tags using regex rules, and enriches missing metadata against the MusicBrainz, Spotify, or Rocksky catalogs. Before forwarding a play to Last.fm, ListenBrainz, Libre.fm, Maloja, Koito, teal.fm, Discord Now Playing, or Tuneshine, the engine checks temporal and title similarity scores to block duplicate scrobbles. When a downstream service goes offline, failed scrobbles enter a persistent retry queue so you never lose listening history, while Gotify, Ntfy, and Apprise webhooks alert you to source issues. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

Document-generation code is the worst kind of code in your backlog - Carbone kills it. Its insight is separating design from data - templates are ordinary office documents (DOCX, ODT, XLSX, PPTX, HTML, even custom XML) built in LibreOffice, Microsoft Office, or Google Docs, with mustache-like markers such as {d.companyName} typed directly into the text. Send a template plus JSON from your existing APIs to the HTTP API, and Carbone returns the finished document - exported as-is or converted to PDF, XLSX, CSV, HTML, PNG, EPUB, and more via its integrated LibreOffice converter (Chromium and OnlyOffice engines are also supported for HTML-fidelity and office-format conversions). The template language goes well beyond substitution: loops over arrays render dynamic table rows, filters and aggregations run inside the document, and built-in formatters handle dates, numbers, currencies, timezones, and locales, with custom JavaScript formatters when needed. One template serves multiple languages through translation markers with auto-maintained translation files. The XML-agnostic engine means anything your document editor can design - pagination, headers, footers, nested tables, charts - survives generation intact, and Carbone guarantees no breaking changes in template syntax. Node.js-based, fast via multi-threaded LibreOffice conversion. The invoices, contracts, and reports your product owes its users become template edits, not sprints.

MateClaw delivers a multi-agent AI platform where digital employees run as persistent team members with roles, goals, and accumulated skills rather than stateless chat completions. The Spring Boot backend on Spring AI Alibaba provides ReAct iterative reasoning and Plan-and-Execute decomposition on a StateGraph runtime, with parallel delegation between employees and dynamic context pruning for multi-step tasks. Five career templates ship ready (Product Researcher, Customer Support, Knowledge Curator, Data Analyst, Executive Assistant) while custom employees inherit configurable backstories, pixel-art avatars, and dedicated tool bindings. The MCP integration supports stdio, SSE, and Streamable HTTP transports with per-employee tool isolation preventing capability bleed between agents. ACP bridges bring Claude Code, Codex, and other coding agents in as first-class employees. Workflow orchestration composes multiple employees and system actions into publishable linear DSL processes with seven step modes: sequential, fan_out, collect, conditional, await_approval, dispatch_channel, and write_memory. The trigger system wires cron schedules, webhooks, channel messages, employee lifecycle events, content matches, and workflow completions to automated flows. The Admin Runtime Console provides real-time visibility into running employees with token usage tracking and one-click force-recycle. Spring Boot Actuator monitoring, full audit trail, and per-channel error isolation deliver production-grade reliability. 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.

Running a single AI agent is straightforward; running a team of specialized agents that delegate tasks, share memory, and coordinate through structured workflows requires an orchestration layer, and that is exactly what SwarmClaw provides. Define a hierarchy of agents in an org chart where a Coordinator (your CEO agent) delegates research tasks to a Researcher, coding tasks to a Developer, and design tasks to a Designer, each configured with its own LLM provider, tool permissions, and skill set. The Task Board presents a Kanban view of all work items across Backlog, Queued, Running, and Completed columns, with each task card showing its assigned agent, tags, due dates, and approval gates that pause execution until a human reviews and approves. Agents execute work using built-in tools for file operations, shell commands, browser automation, and persistent memory, plus any MCP server you connect via stdio, SSE, or streamable HTTP transport. Durable structured sessions support branching logic, repeat loops, parallel branches with explicit joins, and restart-safe run state that survives crashes without losing progress. Over 23 LLM providers ship built-in: Claude Code CLI, OpenAI, Anthropic, Google Gemini, DeepSeek, Groq, Mistral, xAI Grok, Fireworks, Ollama, and more. Connectors push messages to Discord, Slack, and Telegram, while cron schedules and webhooks trigger agent runs automatically. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

With over 2,700 GitHub stars, Auto Company is the first open-source framework that runs a fully autonomous AI company 24/7 — 14 specialized agents modeled after Jeff Bezos (CEO strategy), Werner Vogels (CTO architecture), Charlie Munger (critical analysis), DHH (full-stack engineering), Kelsey Hightower (DevOps), Seth Godin (marketing), and eight more domain experts collaborate through dynamic squad formation to ideate products, write code, deploy infrastructure, and execute marketing campaigns without human intervention. The five-layer architecture separates execution, orchestration, cognition, workflow routing, and observability, while the consensus memory pattern uses a single markdown file as a relay baton between cycles — no vector databases, no Redis, no embeddings required. A bash loop invokes Claude Code or OpenAI Codex CLI every 30 seconds, each cycle selecting 2-5 agents from the 14-person pool based on task context. Over 30 reusable skills handle specialized tasks from frontend design to competitive analysis and deployment automation. Circuit breakers trigger cooldown after consecutive errors, rate-limit detection auto-sleeps on API throttling, and sandbox rollback protects against destructive changes. The Python-powered web dashboard displays real-time cycle status, cost tracking per cycle averaging under $2, and agent activity visualization, with CLI control via make start, stop, monitor, pause, and resume. Supports macOS via launchd, Windows via WSL with systemd, and native Linux deployment. The npx create-auto-co command scaffolds a new AI company in seconds. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.