Autonomous red team execution without manual script coordination is what PentaGI delivers through a multi-agent penetration testing platform engineered for automated security assessments. Security engineers configure testing scopes, target IP ranges, domain lists, and rules of engagement through an interactive web console with real-time execution graphs. Autonomous agent personas break down high-level assessment goals into discrete tactical phases, orchestrating network port discovery, service banner fingerprinting, web application crawling, and CVE verification. Specialized agents query integrated Graphiti knowledge graphs and local vulnerability repositories to synthesize attack paths, validate exploitability, and confirm finding veracity before issuing alerts. Operators monitor live agent terminal streams, inspect sandboxed tool executions, and adjust active LLM provider routes across OpenAI, Anthropic, or local Ollama endpoints. The template editor allows red teams to compose reusable testing playbooks with customizable security prompt chains, safety constraints, and automated remediation reporting. Audit logs capture full command histories, raw tool outputs, and LLM reasoning steps to generate compliance-ready technical documentation. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

Command and automate your entire fleet of 3D printers without relying on proprietary cloud services using Bambuddy, a self-hosted management hub that delivers local network control, print scheduling, and job archiving for Bambu Lab hardware. Print shop operators can route slicing output directly from Bambu Studio or Orca Slicer through virtual printer proxies that emulate physical machines while automatically cataloging print files in a searchable 3D repository. The automated dispatch engine assigns queued gcode files to available printers based on required nozzle temperatures, build plate dimensions, and matched multi-color filament slots. Users can inspect live camera streams across multiple printing beds simultaneously, verify empty build plates before dispatching new jobs, and generate stabilized timelapse videos with custom music. Integrated smart plug connectors automatically cut power to idle machines when print cycles finish and trigger push notifications to Discord or mobile devices if thermal anomalies or mechanical pauses occur. Farm managers can schedule maintenance alerts based on cumulative motor runtime, track spool inventory levels across storage locations, and synchronize printing configurations across duplicate hardware setups. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. GNU AGPL v3.0 licensed.

Sim Studio lets teams build, deploy, and monitor AI agent workflows by dragging blocks onto a visual canvas and wiring them into executable pipelines, backed by over 1,000 integrations. The React Flow editor represents each step as a node: LLM calls, tool invocations, conditional branches, and data transformations form directed acyclic graphs that run as complete agent pipelines. Every major LLM provider works natively, including OpenAI, Anthropic, Google Gemini, Groq, and Cerebras, plus local models through Ollama and vLLM. Integrations span Gmail, Slack, Microsoft Teams, Telegram, WhatsApp, Notion, Google Workspace, Airtable, GitHub, Jira, Linear, Perplexity, Firecrawl, PostgreSQL, Supabase, Pinecone, and Qdrant. Built-in tables provide a database layer, a file store offers shared team storage, and knowledge bases powered by PostgreSQL with pgvector enable retrieval-augmented generation. Finished workflows deploy as REST API endpoints, scheduled jobs, or Slack bots, with block-by-block execution traces for full observability. Real-time collaborative editing via Socket.io supports simultaneous multi-user construction. Alternatively, describe agent behavior in natural language and Sim assembles the workflow automatically. Built on Next.js App Router, Bun runtime, Drizzle ORM, and Tailwind CSS. 29,400+ GitHub stars and 100,000+ builders. Apache-2.0 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.

With over 5,000 GitHub stars since its June 2026 launch, OOMOL OpenConnector bridges the gap between AI agents and the real world by handling the authentication nightmare that stops LLMs from calling external APIs safely. The runtime connects to more than 1,000 SaaS providers — GitHub, Gmail, Notion, Slack, Microsoft, HubSpot, Google Workspace, and hundreds more — through 10,000+ prebuilt typed Actions that agents can discover and execute without ever touching raw credentials. OAuth2 flows, API key rotation, custom credentials, and no-auth providers are all managed centrally with AES-encrypted storage, scoped runtime tokens, and configurable action allowlists and blocklists that enforce least-privilege access. Agents interact through five access surfaces: the Model Context Protocol endpoint at /mcp for Claude and other MCP-capable hosts, a full REST API at /v1 for programmatic control, an auto-generated OpenAPI specification for code generation, a TypeScript SDK for application integration, and the oo CLI for local agent relay. The built-in Web Console provides browser-based administration for configuring OAuth apps, managing connections, inspecting action schemas, and reviewing execution logs with redacted inputs. Deploy via Docker Compose with SQLite for single-server setups, run from source on Node.js 22+, or push to Cloudflare Workers with D1 and R2 for edge deployment. 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.

Open-sourced by the Databricks AI team under Apache 2.0 and reaching over 8,500 GitHub stars within two months of launch, Omnigent introduces the meta-harness concept: a common orchestration layer that sits above existing AI coding agents and makes them interoperable parts of a governed, collaborative system. The platform wraps Claude Code, Codex, Cursor, OpenCode, Hermes, Pi, and any custom agent defined in a simple YAML configuration file into sandboxed sessions with a uniform API, then exposes each session through the terminal, a web UI, a native desktop application, mobile interfaces, and a REST API. Built-in multi-agent workflows include Polly, a coding orchestrator that delegates tasks to parallel sub-agents in separate git worktrees and routes each diff to a reviewer from a different vendor, and Deep Research, which plans sub-queries, searches the live web through MCP servers, reads full pages, and cross-checks claims across independent sources. Contextual security policies go beyond static allow/deny rules by maintaining per-session state to enforce spend caps, model routing, approval gates for destructive actions, PII blocking, and repository-scoped write restrictions across server-wide, per-agent, and per-session levels. The OS sandbox restricts filesystem and network access while intercepting egress requests to inject credentials only on approved calls. Cloud sandbox providers including Modal, Daytona, E2B, CoreWeave, Kubernetes, and Databricks launch disposable execution environments per session. 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.

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.

Deployed at thousands of enterprises across financial services, healthcare, government, and telecommunications, Apache NiFi is the industry-standard platform for building automated data pipelines through a visual drag-and-drop browser interface that requires zero coding for common integration patterns. The flow-based programming model connects over 300 built-in processors covering relational databases via ExecuteSQL and PutDatabaseRecord, Apache Kafka with PublishKafka and ConsumeKafka, HTTP endpoints through InvokeHTTP and ListenHTTP, cloud storage for AWS S3, Azure Blob, and Google Cloud Storage, SFTP/FTP file transfers, and JSON, XML, CSV, and Avro transformations. Data provenance tracking logs every routing decision, transformation, and delivery for every FlowFile, creating a searchable lineage graph from source to destination with full content replay capability for auditing and debugging. Guaranteed delivery uses configurable backpressure thresholds, prioritized queuing with latency or throughput optimization, and automatic retry with exponential backoff, ensuring no data loss even during downstream outages. The zero-leader clustering architecture distributes processing across nodes with automatic load balancing, while site-to-site protocol enables secure data transfer between NiFi instances across network boundaries. Security includes OpenID Connect and SAML 2.0 single sign-on, role-based access control with fine-grained policies per component, and TLS encryption for all communication. Custom processors can be written in Java and packaged as NAR bundles, or implemented directly in Python through the native scripting framework. 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.

Originally built at Netflix to orchestrate microservices powering 230 million subscribers and now trusted in production at Tesla, LinkedIn, and J.P. Morgan, Conductor is the most battle-tested open-source workflow engine available — with 32,000 GitHub stars and horizontal scalability to billions of executions. The architecture cleanly separates orchestration from business logic: workflows are defined in declarative JSON while workers execute tasks in any of seven supported languages (Java, Python, Go, JavaScript, C#, Ruby, Rust) with zero framework constraints. Durable execution persists every state transition, enabling automatic retries, configurable timeouts, crash recovery, and instant replay from any failure point without re-executing completed tasks. Native AI agent orchestration supports 14+ LLM providers (Anthropic, OpenAI, Google Gemini, AWS Bedrock, Mistral, Cohere, HuggingFace, Ollama), MCP tool calling, function calling, human-in-the-loop approval gates, and vector database integration (Pinecone, pgvector, MongoDB Atlas) for RAG pipelines. Deploy with your choice of five persistence backends (PostgreSQL, Redis, MySQL, Cassandra, SQLite), six message brokers, and Elasticsearch or OpenSearch for workflow indexing — all configurable via Docker Compose files included in the repository. The built-in web UI provides workflow visualization, execution monitoring, task queue inspection, and manual intervention controls. 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.

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.

Dify turns the notoriously complex process of building production-grade AI applications into a visual drag-and-drop experience that teams can actually ship and maintain. With over 87,000 GitHub stars and backing from prominent investors, the platform has become the go-to open-source LLMOps solution for organizations that refuse to be locked into proprietary AI stacks. The visual workflow canvas lets developers wire together LLM calls, conditional logic, iteration loops, tool invocations, and human-in-the-loop checkpoints without writing boilerplate integration code. Its RAG pipeline engine handles the full document lifecycle from ingestion of PDFs, Word documents, and HTML through configurable chunking strategies, embedding with models from OpenAI or open-source alternatives, vector storage in Weaviate, Qdrant, Pinecone, or pgvector, and hybrid semantic-plus-keyword retrieval with citation tracking. Dify integrates with hundreds of model providers including OpenAI GPT-4o, Anthropic Claude, Google Gemini, Mistral, Llama, and any OpenAI-compatible endpoint like Ollama for fully local inference. The agent framework supports both ReAct and function-calling strategies with 50-plus built-in tools spanning Google Search, DALL-E, Stable Diffusion, WolframAlpha, and custom API definitions. Published apps can be deployed as hosted web interfaces, embedded chat widgets, REST API endpoints, or MCP-compatible tools. Enterprise features include role-based access control, SSO integration, and audit logging. A built-in marketplace enables teams to share and reuse model providers, tools, and workflow templates across projects. 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 an open-source community edition.

With over 7,400 GitHub stars and benchmarked at 0.89 seconds average session lifecycle — 1.7x to 9x faster than competing browser automation platforms — Steel Browser delivers production-grade headless Chrome infrastructure purpose-built for AI agents that need to interact with the modern web. The TypeScript-based server exposes a REST API providing on-demand browser sessions with full CDP (Chrome DevTools Protocol) access, allowing connections from Puppeteer, Playwright, or Selenium through standard WebSocket endpoints without framework lock-in. Each session maintains persistent state including cookies, localStorage, IndexedDB, and authentication credentials across requests, enabling stateful multi-step agent workflows that survive session restarts. Built-in anti-detection includes stealth plugins, browser fingerprint randomization, and configurable user-agent rotation, while the proxy chain manager handles IP rotation through residential, datacenter, or custom proxy pools. CAPTCHA solving integrates natively so agents encounter fewer blocking interrupts during autonomous navigation. The Session Viewer provides real-time WebRTC-streamed visual debugging of live sessions and playback of recorded sessions with full network request logging. Browser Tools APIs convert any page to clean Markdown, readability-optimized text, PDF documents, or high-resolution screenshots with a single API call. The MCP Server integration exposes Steel sessions as tools accessible to Claude, Cursor, and other Model Context Protocol-compatible AI agents. Deploy via Docker with a single container or use Docker Compose for production configurations with automatic resource cleanup and session lifecycle management. 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.

Your house already has lights, locks, sensors, thermostats, and speakers from many brands, and Home Assistant gives them one local control room with no vendor cloud in the loop. To close the shutters when the outdoor temperature holds above 25 °C, or to be alerted when the garage door is left open, build the routine in the visual editor: When, And if, Then do. Scenes, scripts, and blueprints package it for reuse, and run traces show what it did. More than 1,500 integrations cover Zigbee, Z-Wave, Matter, Thread, MQTT, ESPHome, Bluetooth, Hue, and Sonos, and network discovery offers known devices for one-step setup. To see the house at a glance, drag tile, thermostat, gauge, graph, and map cards into a dashboard, then put it on a TV with Home Assistant Cast. The Energy dashboard answers where the power goes, drawing solar, grid, battery, gas, and water as one distribution diagram with cost totals and per-appliance tracking. To talk to the house, use Assist: natural-language commands, wake words, and custom sentences run locally or through Home Assistant Cloud. The map panel shows who is home, plotting people against zones such as Home, Work, and School from the iOS and Android companion apps. Areas and labels keep large setups tidy, and multi-factor authentication guards each account. 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.

Getting a language model into the chat apps people already use takes a single self-hosted server running AstrBot, which answers in QQ, Telegram, Discord, Slack, Lark, DingTalk, LINE, and WeCom. The model itself is a setting. OpenAI-compatible endpoints, Anthropic, Google Gemini, DeepSeek, Ollama, and LM Studio all work, with fallback models and retry limits for failed requests, and Dify, Coze, or Alibaba Cloud Bailian can take over a conversation too. A bare model cannot act, so the built-in agent calls MCP servers and Skills, delegates to SubAgents, runs scheduled tasks, and executes code in an isolated sandbox. It cannot read your files either, so a knowledge base takes PDF, Word, Markdown, and EPUB uploads and searches them with hybrid dense and BM25 retrieval. Personas shape each bot's personality, and Whisper or Edge TTS adds speech. When an answer looks wrong, the ChatUI shows thinking, tool calls, token counts, and latency, and a per-message trace timeline shows how the bot got there. Because the panel steers the bot, administrator IDs, session whitelists, optional TOTP login, and HTTPS protect it. Backups live under System Settings, and the plugin market installs any of more than 1,000 extensions in one click. 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.

Price drops, restocks, job postings, government announcements, competitor edits - changedetection.io watches web pages and alerts you the moment anything changes, down to PDF text and checksums. Point it at a URL, set a check interval, and precise filters decide what counts as a change: a Visual Selector targets page elements by pointing and clicking, CSS selectors and XPath narrow scope, trigger-text and ignore-text rules (with regex support) cut noise, and JSONPath or jq handles API responses. A dedicated re-stock and price detection mode extracts product metadata and fires on thresholds - alert only when the price drops below your target or the percentage change exceeds a limit. JavaScript-heavy sites render through a real Chrome browser via Playwright, with the ability to execute JS steps first (log in, click, scroll) before extracting text. Notifications reach 85+ services through Apprise - Discord, Slack, Telegram, email, webhooks - optionally with a screenshot of the changed page, and AI-powered summaries (any OpenAI-compatible endpoint, including local Ollama) describe what changed. Per-watch proxies, custom headers, and POST/GET control cover hostile targets. Apache-2.0 licensed with local file-based storage: the URLs you monitor and why stay entirely your business.

A campaign engine wrapped around a contact database: Mautic, the largest open-source marketing automation platform, replaces HubSpot or Marketo without per-contact pricing. Contacts arrive through forms, landing pages, imports, or the REST API and flow into segments: dynamic filters that update automatically from behavior, custom profile fields, or point scores. Segments decide who qualifies; campaigns decide what happens. The drag-and-drop Campaign Builder composes multi-step workflows from actions, positive/negative decision trees, and conditions (field values, tags, device type, segment membership, point thresholds), with static or relative delays, a Jump-to-Step action for moving contacts between branches, and handoffs that push contacts into CRMs or entirely different campaigns. Messaging covers email, SMS, and web/app push out of the box, with A/B testing and a drag-and-drop email builder; dynamic website content swaps page sections per known contact. Lead scoring assigns points for clicks and visits with decay for inactivity, while stages track funnel position. Native integrations cover Salesforce, HubSpot, Zoho, and Dynamics, plus a full REST API for custom sync. It runs on PHP and MySQL with cron jobs processing campaigns and segment rebuilds - self-hosting keeps your entire contact database and behavioral history under your control.

Browser Use Web UI lets you describe a web task in plain English and watch as an AI agent autonomously navigates pages, clicks buttons, fills forms, and extracts information without writing any automation code. Backed by over 16,000 GitHub stars, the Gradio-based interface supports 14+ LLM providers through a unified abstraction layer: OpenAI GPT, Anthropic Claude, Google Gemini, Azure OpenAI, DeepSeek, and local Ollama models are all configurable via dropdown menus without touching code or environment files. The BrowserUseAgent handles interactive single-task automation with step-by-step LLM decision-making and vision-based page understanding, while the DeepResearchAgent orchestrates multi-step research workflows using Langgraph state machines that spawn parallel browser instances with asyncio concurrency control. Custom browser support connects your existing Chrome profile to preserve logins, cookies, and sessions across agent runs, eliminating re-authentication overhead. Persistent browser sessions maintain complete interaction history between tasks for debugging and demonstration. The Docker deployment bundles Chrome, Playwright, and a VNC server in a single container, exposing the Gradio interface on port 7788 and a noVNC viewer on port 6080 for real-time observation of agent behavior. MCP integration via MultiServerMCPClient enables external tool access. Screen recording captures agent workflows as video for review and documentation. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.