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.

GPT Load has become the go-to self-hosted AI gateway for teams managing multiple LLM provider credentials behind a single URL. The Go-built proxy transparently preserves native API formats for OpenAI Chat Completions, OpenAI Responses, Anthropic Messages, and Google Gemini — applications swap one base URL and keep their existing SDK integration untouched. Twenty built-in channels cover official APIs (OpenAI, Anthropic, Gemini, xAI), cloud platforms (Azure OpenAI, AWS Bedrock, Google Vertex AI), model services (DeepSeek, Moonshot AI, SiliconFlow, Zhipu AI, Alibaba Cloud, Volcengine, OpenRouter, Groq), and subscription accounts (Codex, Claude, Antigravity, Grok) using the same credential management, scheduling, and health system. The intelligent key pool rotates among valid credentials using atomic counters for fair high-concurrency distribution, automatically blacklists failing keys after configurable thresholds, and recovers them via scheduled health checks — all transparent to clients. Weighted load balancing distributes traffic across multiple upstream endpoints while per-credential proxies route individual keys through different egress paths. The Vue 3 management dashboard provides real-time statistics, group configuration, key testing, request logs with full debugging context, per-model cost estimates, and route inspection. Docker deployment exposes the management interface and proxy on port 3001 with SQLite by default, MySQL or PostgreSQL optional, and Redis for distributed leader-follower cluster scaling. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT 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.

Open Agent Builder delivers a visual canvas for orchestrating AI agent workflows without writing Python scripts or managing complex codebases. The React Flow-powered drag-and-drop interface supports seven node types — Agent, Scraper, Transform, If/Else, Loop, User Approval, and MCP Tool — each configurable with provider-specific settings for Anthropic Claude (Haiku 4.5 and Sonnet 4.5), OpenAI GPT-5, Groq, or any OpenAI-compatible endpoint. The LangGraph orchestration engine handles state management, conditional routing, and human-in-the-loop approval gates while Firecrawl integration converts any website into structured, LLM-ready data through scrape, crawl, and map operations. E2B sandboxed code execution powers Transform nodes for secure data manipulation without risking host system integrity. Real-time streaming updates show execution progress node-by-node as workflows run, with Convex providing reactive database synchronization for workflow state and execution history. The TypeScript-first architecture (96.8% TypeScript) built on Next.js 16 App Router with Tailwind CSS delivers a responsive interface across devices. Clerk handles multi-user authentication with JWT integration for secure workspace isolation. Deploy via npm install and environment configuration with Firecrawl, Convex, and Clerk API keys. 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 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.

Agenta delivers a comprehensive open-source LLMOps workspace that covers the full lifecycle of AI application development — from prompt engineering through production monitoring. The platform supports 15+ model providers including OpenAI, Anthropic, Google Gemini, Mistral, Groq, Together AI, Azure, AWS Bedrock, and self-hosted models via Ollama, enabling teams to switch between providers without code changes. The prompt playground allows side-by-side comparison of different configurations, while the evaluation system offers LLM-as-a-Judge assessment, 20+ pre-built evaluators covering semantic similarity, regex matching, and factual accuracy, plus custom Python evaluators for domain-specific requirements. Teams run evaluations through both the web UI for subject matter experts and the Evaluation SDK for programmatic CI/CD integration. The observability layer captures full trace visibility across complex agentic workflows, flagging quality issues like hallucinations and off-topic responses in real time. Human annotation workflows let domain experts review and annotate LLM outputs, feeding corrections back into the evaluation loop. The architecture supports Chain of Prompts, RAG pipelines, and multi-step agent workflows, integrating with frameworks like LangChain and LlamaIndex. Self-hosting deploys via Docker Compose with Traefik for routing, requiring only a clone, environment configuration, and a single docker compose command. On RepoCloud, deploy Agenta on a dedicated VPS with root SSH access, persistent storage for evaluation datasets and traces, and complete control over model provider credentials, all under the MIT license with no usage restrictions.

With 2,000 GitHub stars and 10 releases since its September 2025 launch, HeadlessX delivers a self-hosted browser automation platform that replaces Chromium-based scraping with Camoufox — a Firefox fork performing kernel-level fingerprint spoofing to achieve 0% detection across Cloudflare, DataDome, PerimeterX, and other anti-bot systems where Puppeteer and Playwright regularly fail. The web dashboard provides workspace-based job organization with a visual interface for configuring scrape targets, managing browser profiles, monitoring queue status, and viewing extracted results in real time. The protected REST API accepts requests with API key authentication for programmatic access, supporting HTML extraction, screenshot capture, PDF generation, and structured data parsing with configurable stealth parameters. Profile-based scraping maintains persistent browser contexts with cookie jars, localStorage, and fingerprint configurations that survive between requests — reducing cold-start latency from 25 seconds to under 2 seconds on subsequent requests. Queue-backed workflows enable batch processing of URLs with configurable concurrency, retry logic, and webhook notifications on completion. The Google AI Search integration provides AI-assisted web research workflows through dedicated endpoints. Remote MCP support exposes automation capabilities as tool endpoints for AI agent integration. Deploy via the official CLI with `headlessx init` and `headlessx start` commands, scaffolding a Docker Compose stack with Caddy reverse proxy for automatic HTTPS. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

LearnHouse delivers a modern open-source learning platform that replaces proprietary course builders with a self-hosted alternative shipping a rich feature set out of the box. The Tiptap-powered block editor supports videos, documents, embeds, quizzes, and file uploads in a Notion-like interface with real-time co-editing powered by Hocuspocus and Yjs CRDT synchronization over WebSocket. AI tutoring integrates Google Gemini and LlamaIndex for RAG-powered context-aware assistance that adapts to course content, while interactive Playgrounds use AI to generate simulations, diagrams, and learning exercises. The platform handles the full course lifecycle: chapters and activities organize into collections and learning paths, assignments support automated and manual grading, and code blocks execute student submissions in 30+ languages with auto-grading. Analytics dashboards track learner engagement, progress, and completion rates in real time. The backend runs on FastAPI with SQLModel and Alembic migrations against PostgreSQL 16 with pgvector for AI embeddings, while Redis handles caching and session management. The frontend builds on Next.js 16 with React 19 and Tailwind CSS v4. Deployment uses an interactive CLI wizard that configures domain, database, admin account, SSL via Let's Encrypt, and optional features like email via Resend, S3 storage, and Google OAuth, then generates a Docker Compose stack ready to start. On RepoCloud, deploy LearnHouse on a dedicated VPS with root SSH access, persistent PostgreSQL storage for your course data, and complete control over AI provider keys and branding customization, all under the AGPL v3 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.

Describe a component in natural language and watch it render: OpenUI, from Weights & Biases, is an open alternative to Vercel's v0. Type a prompt like "a dark-themed dashboard with a sidebar and charts" and the LLM renders working HTML with Tailwind styling live in the browser. You then iterate conversationally, asking for changes until the design is right, and convert the result to React, Svelte, or Web Components for use in a real project. The backend is Python with LiteLLM routing, so it works with OpenAI, Anthropic, Gemini, Groq, and Mistral API keys, or fully offline against local Ollama models, including vision models like LLaVA that can generate UI from screenshot input - feed a screenshot and the model reproduces or riffs on an existing interface. Generated markup is inspectable at any point, with light and dark mode toggles, theme selection, and responsive previews across device sizes. The practical effect is compressing the mockup-review-revise loop from hours to minutes: a described layout renders in seconds and iterates through follow-up prompts, and because output converts to real framework code, prototypes feed directly into production codebases instead of staying trapped in a design tool. Self-hosting keeps unreleased product interfaces and prompts on your own server, and LiteLLM routing lets you pick the model per task - a cheap fast model for rough drafts, a stronger one for final passes, or free local models for unlimited experimentation.

With 15,500 GitHub stars and over 1,100 forks, Plandex delivers a terminal-based AI coding agent purpose-built for the complex, multi-file tasks that overwhelm single-file AI assistants. The Go-powered server maintains a cumulative diff review sandbox that quarantines all AI-generated changes from your project files until you explicitly approve them — enabling 20-file refactors where you cherry-pick good changes and reject bad ones without touching git. A 2M token effective context window loads only what each step requires, while tree-sitter project maps index repositories exceeding 20M tokens across 30+ programming languages, providing structural awareness of class hierarchies, function signatures, and import graphs without burning tokens on full file content. The configurable model pack system assigns different models to different roles — Claude for planning, GPT for coding, Gemini for summarization — supporting Anthropic, OpenAI, Google, OpenRouter, Azure OpenAI, AWS Bedrock, DeepSeek, Perplexity, and Ollama for local models. Full auto mode handles end-to-end autonomous workflows including high-level planning, context loading, implementation, terminal command execution, and automated debugging of both terminal and browser applications. The interactive REPL provides fuzzy auto-complete, version-controlled sandbox branching, rewind to any previous point, and Git integration for commit message generation. The Plandex Server exposes 60+ REST API endpoints for programmatic orchestration across organizations, projects, plans, and branches. Deploy via Docker Compose for self-hosted operation with your own API keys. 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 nearly 5,000 GitHub stars earned in under two years, WhoDB has rapidly emerged as the lightweight alternative to heavyweight database clients like DBeaver and DataGrip by delivering a sub-50MB binary that starts in under a second and connects to 18+ database systems from a single interface. The Go backend serves the React and TypeScript frontend with table virtualization for efficient rendering of large result sets, lazy loading, and query result streaming that keeps the interface responsive even when browsing tables with millions of rows. The Community Edition connects to PostgreSQL, CockroachDB, YugabyteDB, MySQL, MariaDB, TiDB, SQLite, DuckDB, MongoDB, FerretDB, Redis, Valkey, Dragonfly, Elasticsearch, OpenSearch, ClickHouse, QuestDB, and Memcached through a unified credential selector that switches between databases with minimal configuration. Interactive schema diagrams render entity-relationship graphs showing table structures, foreign keys, and column types for visual database exploration. The Jupyter-style query scratchpad provides SQL autocomplete, syntax highlighting, and multi-statement execution with paginated results. AI integration optionally connects to Ollama, OpenAI, Anthropic, LM Studio, or any OpenAI-compatible provider for natural language database queries — ask questions in plain English and receive generated SQL. Data management includes inline row editing, CSV export, and filtered data views. Docker deployment runs a single container exposing port 8080. 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 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 nearly 600 GitHub stars and a feature set that rivals commercial note apps, Glass Keep is the self-hosted Google Keep alternative that wraps a full-featured notes system in a glassmorphism UI with blurred backdrops, translucent modals, and smooth transitions. The React and Vite frontend renders notes in a masonry card grid with pinning, color themes, tag chips, and drag-and-drop reordering. Text notes support Markdown with headings, bold, italic, strikethrough, blockquotes, and fenced code blocks, while checklists offer inline editing, drag-to-reorder items, and direct toggle from the grid without opening the note. A freehand drawing mode provides customizable brush sizes and colors for handwritten notes. The private AI assistant runs an optimized Llama 3.2 (1B) model entirely inside the Docker container using RAG over your own notes, answering queries like "what are my AWS commands?" without any data leaving your server. Deep search spans titles, Markdown text, tags, checklist items, and image names. Import notes from Google Keep via Takeout JSON files or export your entire vault as JSON with per-note Markdown downloads. The Express backend with better-sqlite3 requires no external database. Real-time collaboration enables shared checklists with live item toggling. Dark and light themes persist across sessions, and the PWA manifest supports installation on any device. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

A clean alternative to n8n and Zapier that puts AI-native workflows front and center, Fynt is the MIT-licensed workflow automation platform where you drag nodes onto a React Flow canvas, wire them together with typed connections, and let a distributed BullMQ engine execute them — with every step streamed live to your browser over WebSockets so you never wonder what happened inside a run. The node library spans triggers (manual, webhook, cron scheduling), AI providers (OpenAI, Anthropic, and Gemini with structured output parsing), service integrations (GitHub webhooks, Notion databases, Slack channels, Discord bots, arbitrary HTTP endpoints), logic gates (conditional branching, filtering, data transformation), and utility nodes (delay, logging, payload mapping). The execution architecture separates concerns across three services: a Next.js 16 web application serving the React 19 workflow builder and tRPC API, a BullMQ worker processing jobs with node-level retries and checkpointing for crash-safe execution, and a dedicated WebSocket relay server broadcasting real-time run events via Redis Pub/Sub. All stored credentials are encrypted at rest using AES-256-GCM with per-credential initialization vectors. The full-stack deploys as a single Docker Compose stack (web, worker, realtime, PostgreSQL, Redis) or individually via pnpm workspaces in a Turborepo monorepo. Authentication is handled through better-auth with configurable OAuth providers. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

This is a marketing operations control center that replaces fragmented CRM, outreach, content, and analytics tools with a unified self-hosted interface designed for AI agent-assisted go-to-market teams. The CRM module manages leads through a configurable pipeline funnel with stages from New through Sequenced, Replied, Interested, and Booked, tracking source attribution, industry segments, company size, lead quality scores, and LinkedIn URLs per contact. Outreach sequencing supports email campaigns with pause controls, audit endpoints, suppression workflows, and engagement tracking. The content operations surface provides calendar views, content item management, performance metrics, and approval queues for editorial control. Analytics and KPI dashboards show impressions, engagement, and send volumes over configurable time periods, with optional connectors to Plausible, Google Analytics 4, X, and LinkedIn for cross-platform reporting. The OpenClaw-native agent runtime enables dynamic agent and squad discovery, workspace management, session monitoring, and communications surfaces. Automation scheduling uses cron job templates with OpenClaw-compatible schedule variants including cron expressions, every intervals, and at timestamps. The tech stack combines Next.js 16 App Router with React 19, Tailwind CSS 4, Recharts, and Zustand for state management. Authentication supports session cookies, API keys, and optional Google OAuth with role-based access controls. All state persists locally in SQLite via better-sqlite3 with no required external infrastructure. On RepoCloud, deploy Marketing Dashboard on a dedicated VPS with persistent SQLite storage, root SSH access, and complete control over your marketing operations data, all under the MIT license.

OpenCode Manager is a mobile-first command center for AI coding agents. Install the PWA on your phone or tablet and you get real-time streaming chat, multi-repository Git operations, and scheduled automation right in your pocket. Git integration handles SSH-authenticated repo cloning, worktree management, unified diffs, and branch operations across all your projects in one dashboard. Chat with coding agents through Server-Sent Events streaming that supports slash commands, @-mentions for files, Plan and Build modes, and Mermaid diagram rendering for architecture discussions. Schedule reusable prompts to run against any repository on intervals or cron expressions, with each run tracking history and linking to sessions so you can pick up exactly where automation left off. MCP server configuration adds local and remote HTTP servers with OAuth support, plugging into the broader Model Context Protocol ecosystem. A dedicated assistant workspace provides an isolated AI environment with auto-provisioned skills for managing schedules, notifications, and settings. Multiple AI providers are supported including Anthropic, GitHub Copilot, and OpenAI-compatible services, each configurable with custom system prompts and granular tool permissions. Push notifications alert you to session events, agent questions, errors, and task completions across all managed repositories.

Zapier's job, on your own server: Activepieces is an open-source workflow automation platform built to be exactly that replacement. Flows are built in a visual no-code editor with triggers, actions, loops, conditional branches, auto-retries, raw HTTP steps, and code steps that run JavaScript or TypeScript with full npm package support. Integrations are "pieces" - type-safe TypeScript npm packages with hot reloading for local development - and the catalog spans 600+ services, with the large majority contributed by the community. The platform is AI-first in two directions: native AI pieces call OpenAI, Anthropic, Google, and Azure models inside flows, and every piece automatically doubles as an MCP server, so assistants like Claude Desktop and Cursor can invoke your integrations and workflows through natural language. A built-in MCP server also exposes 30 tools for building flows, managing tables, and running tests agentically. Flows are fully versioned with draft and locked states. The core is MIT-licensed and runs on TypeScript with PostgreSQL and Redis.