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.

Scoring 64.4 on the WebBench benchmark — state-of-the-art among browser automation platforms — Skyvern replaces brittle XPath-based scripts with Vision LLM reasoning that adapts when websites change their layouts. The platform extends Playwright with AI-powered page methods including page.act(), page.extract(), and page.validate() that accept natural language prompts while still supporting traditional CSS selectors as fallback. The drag-and-drop Workflow Studio offers 17+ block types including navigation, extraction, login, loops, conditionals, code blocks, file download, and file upload — enabling non-technical users to build complex multi-step automations without writing code. Self-hosted deployments support bring-your-own-LLM with OpenAI, Anthropic, Gemini, and Ollama, while the multi-engine architecture allows swapping between Skyvern 2.0, OpenAI CUA, Anthropic CUA, or UI-TARS per task with a single parameter. Built-in infrastructure handles persistent browser sessions preserving cookies and localStorage across runs, automatic CAPTCHA solving for reCAPTCHA and hCaptcha, anti-bot bypass for Cloudflare and DataDome, residential proxy rotation across 20+ countries, and a credential vault integrating with Bitwarden and 1Password for secure 2FA management. Real-time session livestreaming via WebRTC enables visual debugging, while step-by-step action logs with screenshots and full LLM diagnostic traces provide production observability. The MCP server integration exposes Skyvern as a tool for Claude, Cursor, Windsurf, and any MCP-compatible AI agent. Connect to 6,000+ apps through Zapier, Make.com, or self-hosted N8N workflows. Deploy via Docker Compose or pip install with a two-command setup. 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.

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.

With over 15,900 GitHub stars and 40,000 weekly npm downloads in its first two months, OpenWiki from LangChain has rapidly become the standard for AI-generated codebase documentation. Built on the Deep Agents framework, it deploys a documentation agent that reads your repository's source code, tests, and configuration, then synthesizes a complete linked Markdown wiki with architecture overviews, integration guides, data-flow diagrams, and validated Mermaid visualizations. Two operating modes cover distinct workflows: code mode generates repository documentation in an openwiki/ folder with automatic AGENTS.md and CLAUDE.md integration for Codex, Claude Code, OpenCode, and Cursor, while personal mode builds a local knowledge base from nine connectors including Notion, Slack, Gmail, X/Twitter, Hacker News, LangSmith, Custom MCP, Web Search, and local git repositories. Thirteen model providers are supported out of the box — OpenAI, Anthropic, Gemini, AWS Bedrock, GitHub Copilot, OpenRouter, Nebius, Fireworks, Baseten, NVIDIA NIM, and any OpenAI-compatible endpoint like Ollama or LM Studio. Grounded Claims track every material assertion back to versioned source evidence, flagging stale propositions before they propagate. The interactive visualizer renders wiki pages as an explorable node graph with a side-by-side Markdown reader, exportable as a static site for GitHub Pages or MkDocs. Self-updating CI workflows via GitHub Actions, GitLab CI, or Bitbucket Pipelines open documentation PRs automatically when code changes. 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.

With 3,100+ GitHub stars, CyberScraper 2077 replaces brittle CSS selectors and XPath queries with natural language data extraction powered by Large Language Models. Users paste a URL, describe the data they want in plain English, and the AI extracts structured results from any website — no HTML parsing knowledge required. The tool supports three LLM backends: OpenAI GPT models for maximum accuracy, Google Gemini for cost-effective extraction, and local Ollama instances for fully private scraping where URLs and data never leave your server. Built on Python asyncio with Playwright browser automation, it handles concurrent page fetching with content-based and query-based LRU caching to minimize redundant API calls. The Streamlit web interface runs on port 8501 and provides one-click export to JSON, CSV, HTML, SQL, Excel, and direct Google Sheets upload. Tor network integration routes requests through onion routing for anonymous scraping of both clearnet and .onion hidden service sites with automatic circuit management and stream isolation. Stealth mode randomizes user agents, manages cookies, and controls JavaScript execution timing to bypass bot detection systems. Multi-page scraping navigates through paginated results with automatic URL pattern detection. Docker deployment packages all dependencies including Playwright browsers into a single container. 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 46,000 GitHub stars and one of the largest communities in data engineering, Apache Airflow is the workflow orchestration platform that lets teams define, schedule, and monitor complex data pipelines as Python code through directed acyclic graphs. Airflow 3.x introduced a modernized architecture with a task execution API, the Language Task SDK for writing task implementations in Java and Go alongside Python, asset-based partitioning with FanOutMapper and FixedKeyMapper for data-driven scheduling, a first-class state store for tasks and assets, pluggable retry policies, and a redesigned React-based web UI built on FastAPI. The provider ecosystem ships 80+ packages covering AWS, Google Cloud, Azure, Snowflake, Databricks, Apache Spark, Apache Kafka, PostgreSQL, MySQL, MongoDB, Slack, HTTP, SSH, Docker, Kubernetes, and dozens more, enabling a single deployment to orchestrate jobs across multi-cloud and on-premises infrastructure. The scheduler supports cron expressions, timetable plugins, data-aware scheduling triggered by asset events, and dynamic task generation through Python loops and conditionals. Built-in operators include BashOperator, PythonOperator, DockerOperator, KubernetesPodOperator, and sensor operators that poll external systems. The web UI provides DAG visualization with Gantt charts, grid views, and graph views, task instance logs, SLA monitoring, connection and variable management, and role-based access control. Deployment options include standalone mode, Docker Compose with CeleryExecutor or KubernetesExecutor, Helm charts for Kubernetes, and managed cloud services. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. Apache License 2.0 licensed.

OmniRoute is an AI gateway, aggregating 338 LLM providers including OpenAI, Anthropic Claude, Google Gemini, DeepSeek, Kimi, MiniMax, and GLM into a single OpenAI-compatible endpoint at localhost:20128. The gateway catalogs over 1,200 models across 90 free-tier providers and 40 free-forever providers, automatically rotating through tier-1, tier-2, and tier-3 fallback chains when any provider exhausts its quota or returns errors. RTK plus Caveman stacked token compression reduces eligible context by 15 to 95 percent before forwarding requests, cutting API costs dramatically without degrading output quality. OmniRoute exposes its full routing engine through a built-in MCP server with 104 tools across 31 scopes over stdio, HTTP, and SSE transports, plus an A2A protocol server with six autonomous agent skills and JSON-RPC 2.0 streaming. The gateway integrates directly with Claude Code, Cursor, GitHub Copilot, Codex CLI, OpenCode, and Cline through standard base-URL configuration. Seventeen routing strategies include latency-optimized, cost-minimized, and auto-scoring modes that evaluate candidates on success rate, context fit, model fitness, quota state, and circuit-breaker health. The Next.js dashboard provides real-time provider status, usage analytics, combo chain configuration, and model catalog browsing via a responsive PWA. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT 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.

MeterSphere is the open-source continuous testing platform that brings test management, API testing, and AI-powered automation into a single self-hosted environment. The Spring Boot Java backend handles test execution with the JMeter engine while the Vue.js frontend delivers a responsive interface for managing test cases, plans, defects, and reports across projects. The built-in AI assistant leverages large language models to auto-generate functional test cases and API interface definitions, reducing manual test creation effort. Test management covers the complete lifecycle from writing and reviewing cases in list or mind-map views, through test plan creation with single plans and plan groups, to defect tracking with customizable templates and workflow rules. API testing combines Postman-like ease of use with JMeter-level flexibility, supporting interface debugging with server-side and local execution, API definition with visual request and response editors, interface mocking with configurable headers and body parameters, scenario automation with visual orchestration, and detailed test reports with automatic generation. The system-organization-project hierarchy supports up to 30 users in the community edition with role-based access control, file management, and configurable notification channels. MySQL stores application data, Kafka handles message queuing, MinIO provides S3-compatible object storage, and Redis manages caching. The plugin marketplace extends testing capabilities and enables DevOps pipeline integration. On RepoCloud, deploy MeterSphere on a dedicated VPS with Docker, root SSH access, and complete control over your testing infrastructure, all under the GPLv3 license.

Drag nodes onto a canvas and ship an LLM app: Flowise is an open-source visual builder for AI agents and LLM applications, written in Node.js on LangChain.js and licensed Apache-2.0. You assemble flows by dragging nodes onto a canvas: models, prompts, memory, vector stores, retrievers, and tools, then wire them together and test in the built-in chat panel. Three builder types cover increasing complexity: Assistant for simple RAG chat over uploaded files, Chatflow for single-agent systems with techniques like rerankers and Graph RAG, and Agentflow for multi-agent orchestration with branching, looping, shared flow state, and human-in-the-loop checkpoints. Over 100 integrations connect data sources, vector databases, and both proprietary and open-source models, plus MCP client and server nodes for standard tool interop. Finished flows are exposed as REST APIs, embedded chat widgets, or via JS and Python SDKs - each flow gets an endpoint the moment it is saved, removing the deployment gap between a working prototype and something your application can call. Execution logs, visual step debugging, and external log streaming trace behavior, while input moderation and rate limiting act as guardrails; RBAC, SSO, and workspaces cover team deployments. Self-hosting keeps prompts, encrypted credentials, and conversation data on your own instance, which matters when flows handle internal documents or customer data - and wiring a model, prompt, memory, and vector store on the canvas replaces the boilerplate a hand-coded LangChain project would need.

Replacing HubSpot, Zendesk, Intercom, and Linear with a single self-hosted platform, erxes delivers an Experience Operating System trusted by over 4,000 GitHub stars and built on a modern Nx-powered monorepo architecture. The core ships with six foundational modules — My Inbox for omnichannel conversations across email, web chat, voice, and Discord; Contacts for unified customer profiles; Products for catalog management; Segments for behavioral targeting; Automation for visual workflow builders; and Documents for template generation. Beyond the core, a plugin marketplace activates Frontline for ticket management and omnichannel support queues, Sales for deal pipelines and lead scoring, Operations for project boards with cycle management, Content for headless CMS and knowledge bases, and Team for employee directories, time clocks, and internal chat. The technical stack combines GraphQL Federation with Apollo Server v4 and tRPC v11 microservices on Node.js, React 18 micro-frontends via Rspack Module Federation with TailwindCSS 4, MongoDB with Mongoose for persistence, Redis for caching, BullMQ for job queues, and Elasticsearch for full-text search. Deployment supports Docker Compose orchestration with automatic service discovery across all plugin containers. The Global Profile architecture enables agencies to manage multiple client brands under a single login with separated data stores. iOS and Android SDKs embed the messenger widget directly into mobile applications. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. AGPLv3 licensed.

A question goes in; a cited, long-form report comes out - GPT Researcher is an open-source autonomous research agent. A planner agent decomposes the query into sub-questions, execution agents crawl 20+ web sources in parallel with JavaScript-enabled scraping, and a publisher aggregates findings into a 2,000+ word report with inline citations, exportable to PDF, Word, and Markdown. The Deep Research mode extends this recursively: each result yields follow-up questions that are explored to configurable breadth and depth in a tree pattern, while accumulated learnings, citations, and visited URLs are shared across branches. It also researches local documents (PDF, CSV, Word) alongside the web. LLM and search providers are pluggable, including OpenAI, Anthropic, Google, DeepSeek, and Ollama for models, and Tavily, Google, Bing, DuckDuckGo, and SearXNG for retrieval. It ships as a Python package, a FastAPI server with web frontend, a Docker image, and an MCP server for use inside Claude or Cursor. MIT-licensed.

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.

Backed by Alibaba's AIDC team and carrying over 27,700 GitHub stars, Pixelle-Video turns a single text prompt into a publish-ready short video in approximately three minutes — handling scriptwriting, image generation, voice narration, music selection, subtitle overlay, and final MP4 export in one automated pipeline. The engine supports multiple LLM backends for script generation including GPT-4, Qwen, DeepSeek, and local Ollama deployments, while image and video creation routes through either self-hosted ComfyUI workflows, cloud-based RunningHub pipelines, or direct API connections to DashScope Wan, OpenAI, Seedream, Seedance, and Kling AI. Text-to-speech synthesis uses Edge-TTS, Index-TTS, and other mainstream engines with multi-language voice profiles. Five distinct pipelines cover Quick Create, Standard, Digital Human Avatar broadcasting, Image-to-Video transformation, and Motion Transfer from reference video. The Streamlit web UI on port 8501 provides a visual workflow builder with template selection across portrait (1080x1920), landscape (1920x1080), and square formats, while the FastAPI server on port 8000 exposes a REST API with endpoints for async video generation, task polling, content scripting, TTS and image generation, template listing, and health checks. History persistence tracks all completed generations. HTML-based visual templates support static, image-overlay, and AI-video styles with customizable prompt prefixes. The modular architecture lets operators swap any atomic capability — image model, video model, TTS engine, or VLM — by editing a workflow JSON file without touching Python code. 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.

The first open-source substrate for enterprise knowledge engineering that learns passively and governs itself. The Rust-built backend paired with PostgreSQL and pgvector delivers a bitemporal knowledge graph where every fact carries two timelines: when it held in the real world and when the system came to believe it — enabling full audit trail replay of how understanding evolved. Document ingestion handles PDF, DOCX, PPTX, XLSX, CSV, Markdown, HTML, and plain text with legacy encoding detection, while scheduled syncing pulls from web pages, RSS feeds, GitHub, Jira, Notion, WebDAV, and S3-compatible buckets. Search fuses Tantivy full-text indexing with pgvector semantic vectors using Reciprocal Rank Fusion, streaming answers with inline citations that link directly to source passages. The built-in agent harness drives agentic RAG through conversation — searching documents, walking the knowledge graph at any historical date, and querying mounted databases via Ontology2SQL which achieves state-of-the-art results on BIRD Mini-Dev benchmarks. Five ontology packs ship inside the binary (schema.org, W3C Org, PROV-O, FOAF, IOF Core) with forward-chaining reasoning for transitivity, symmetry, inverses, and relation hierarchy. Entity resolution operates in three stages: exact name matching, embedding similarity, then model-based judgment with every merge reversible. Any OpenAI-compatible endpoint works including DeepSeek, Qwen, Ollama, and vLLM for fully air-gapped 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.

With over 7,700 GitHub stars and thousands of Cloudflare employees using it daily across every function, Cloudflare OS delivers an open-source AI workspace where every employee gets a personal agent grounded in company context, systems, and skills — not a generic chatbot but a programmable workspace that builds real applications, automates workflows, and connects to internal tools through governed access. The Code Mode agent writes and immediately executes code snippets to perform arbitrary tasks, build full-stack Gadgets with client code, server code, APIs, and durable SQLite state, debug errors, and test results within isolated sandboxes. Gadgets are private application instances running in separate sandboxes — each document, spreadsheet, or tool is its own secure runtime that cannot leak data even to attackers with access to other Gadgets. Blueprints enable sharing application code as templates that others instantiate with independent state, credentials, and resources. Gatekeepers provide security governance giving system owners precise control over what agents can see, change, and when human approval is required before actions execute. Built on Cloudflare Workers using Durable Objects for workspace persistence, Dynamic Workers for Gadget execution, and Facets for access management. Zero Trust security via Cloudflare Access verifies every user and request before granting access. Real-time collaboration lets colleagues use shared Gadgets. Deploy to your own Cloudflare account or self-host on workerd, the open-source Workers runtime, on your own servers. 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.