OpenDeepWiki transforms code repositories from GitHub, GitLab, Gitee, Gitea, and AtomGit into structured, searchable knowledge bases by leveraging Microsoft's Semantic Kernel for AI orchestration across OpenAI, Azure OpenAI, Anthropic, and DeepSeek providers. The three-phase Gather-Think-Write pipeline analyzes repository tree structures, generates README summaries, project overviews, wiki catalogs, and document content while producing Mermaid mind maps and optional Graphify visualization artifacts. Repository-scoped MCP endpoints at /api/mcp/{owner}/{repo} expose indexed knowledge to external AI tools, while the built-in chat assistant, embedded chat APIs, and share links provide conversational access to repository understanding. The Next.js 16 frontend serves public documentation on SEO-friendly routes with multi-language translation support, and the admin console manages repositories, users, roles, API keys, AI provider and model configuration, skills, and GitHub App imports. Background workers handle incremental updates using LibGit2Sharp to keep documentation synchronized with evolving codebases, while Polly integration provides transient failure retry handling for LLM requests. The platform supports SQLite, PostgreSQL, and MySQL database backends with Entity Framework Core 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.

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.

Backed by Y Combinator (S24) and processing traces from thousands of AI agents in production, Laminar is the open-source observability platform that treats agent debugging as a first-class engineering discipline rather than an afterthought. Its OpenTelemetry-native SDK auto-instruments Vercel AI SDK, LangChain, OpenAI, Anthropic, Gemini, Browser Use, Stagehand, Mastra, Pydantic AI, and the OpenAI Agents SDK with a single line of code, capturing every LLM turn, tool call, and sub-agent delegation as nested spans with full input/output data and token costs. The Signals engine lets you describe failures in plain language — "agent is stuck in a loop" or "tool returned empty results" — then reads every trace and alerts via Slack when it detects a match. A built-in debugger records runs and replays them from cache so each iteration takes seconds, designed for Claude Code, Cursor, or Codex to drive the repair loop via the MCP server or CLI. Run code-first evaluations in Python or TypeScript locally or in CI/CD pipelines, build datasets from production traces, and query everything with raw SQL through custom dashboards, the in-app editor, or your coding agent. The Rust backend delivers 20x trace compression, a custom real-time streaming engine, ultra-fast full-text search, and gRPC ingestion, while ClickHouse powers columnar analytics and PostgreSQL stores application state. 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.

Bring your own API keys and work with OpenAI GPT models, Anthropic Claude, Google Gemini, Mistral, DeepSeek, Grok, Azure endpoints, and local models in one organized workspace: TypingMind is a unified chat frontend for large language models, replacing a browser tab per provider. Parallel chat sends the same prompt to multiple models and compares answers side by side, and models can be switched mid-conversation. A prompt library stores reusable, tagged prompts with variables, and the AI Agents system builds specialized assistants that bundle a base model, custom instructions, assigned plugins, and uploaded knowledge files for RAG. Plugins extend every connected model with web search, image generation (DALL-E, Stable Diffusion), Deep Research, URL reading via Firecrawl, and Zapier automation - plus MCP server integrations for Notion, Atlassian, and other external tools, and a JavaScript extension API for custom behavior. Chats store locally by default with optional sync. Self-hosting puts the interface on your own domain and, for teams, adds branding, member access limits, and shared prompt and agent libraries.

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.

Recognized by the CNCF Landscape in the AI Agent – Workflow Orchestration category alongside Dify and Temporal, Astron Agent is iFLYTEK's fully open-source platform for building, deploying, and managing enterprise multi-agent systems — backed by 8,900+ GitHub stars and the production infrastructure behind one of China's largest AI companies. Unlike pip-install frameworks such as LangGraph, CrewAI, or AutoGen, Astron Agent ships as a complete microservices platform spanning 10+ services across Java, Python, Go, and TypeScript: a ReactFlow-based visual workflow builder for low-code agent orchestration, native integration with the Model Context Protocol (MCP) for tool calling, a built-in model management layer supporting iFLYTEK Spark, OpenAI, Anthropic, and on-premises MaaS deployments, and a multi-tenant Go authentication service powered by Casdoor. The standout differentiator is native RPA integration via the companion astron-rpa project (7,200+ stars), providing 300+ pre-built automation capabilities spanning browser, Office document, and enterprise system interaction — enabling agents to execute physical UI actions rather than only API calls. Infrastructure includes PostgreSQL for multi-tenant data isolation, MySQL for application metadata, Kafka for event streaming, Redis for caching, and MinIO for object storage, all orchestrated through Docker Compose with explicit health checks and dependency chains or production Kubernetes Helm charts. 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 Y Combinator with 4,300 GitHub stars and growing rapidly since its September 2024 launch, Briefer delivers the first truly unified notebook-and-dashboard platform that eliminates the fragmented workflow of juggling Jupyter for analysis, Tableau for visualization, and Notion for documentation — combining all three in a single Notion-like workspace where SQL query results automatically become Python DataFrames accessible in subsequent code blocks. The built-in AI analyst understands your database schema and notebook context to generate SQL queries, write Python transformations, create visualizations, and fix errors on demand using configurable OpenAI or private LLM backends. Connect directly to PostgreSQL, MySQL, BigQuery, Redshift, Snowflake, and Amazon Athena as data sources, or upload CSV files for immediate analysis. Native point-and-click visualizations produce charts, tables, and dashboards without writing code, while interactive data apps use inputs, dropdowns, and date pickers to create parameterized reports for non-technical stakeholders. Scheduled execution runs notebooks and dashboards periodically with results delivered via Slack integration or public shareable links. Write-back queries modify production data directly from notebooks for ad-hoc pipeline testing. The architecture runs as three Docker containers — web frontend, API server, and optional AI service — backed by PostgreSQL and a Jupyter server for Python execution, deployable via single Docker command, Docker Compose, or Helm charts for Kubernetes. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. AGPLv3 licensed.

With over 8,000 GitHub stars and continuous development since 2020, LibrePhotos delivers the core intelligence of Google Photos — face recognition, object detection, semantic search, and automatic album generation — entirely on your own hardware without sending a single photo to a third-party server. The Django 5 backend processes uploaded media through a machine learning pipeline that runs face detection via the face_recognition library, clusters identified faces using scikit-learn and HDBSCAN, generates image captions through BLIP and Moondream 2, and classifies scenes using Places365 or Google's SigLIP 2 vision-language model with zero-shot classification against 900+ real-world tags. Semantic search lets you find photos by natural language queries like "sunset at the beach" without manual tagging, while metadata search filters by person, camera, lens, file type, and filesystem path. The React 18 frontend built with Vite presents a timeline view, fullscreen lightbox with slideshow mode, photo detail sidebar showing location and people, and a folder navigation view with breadcrumb paths. RAW files from any camera are converted via ImageMagick, videos processed through FFmpeg, and Live Photos paired with their RAW+JPEG counterparts as unified entries. Public album sharing via link provides fine-grained privacy controls, and duplicate detection uses perceptual hashing to identify near-identical images. Deployment runs as a single unified Docker container or via Docker Compose with Kubernetes manifests also available. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

Inference Gateway puts a single OpenAI-compatible API endpoint in front of OpenAI, Anthropic, Groq, Cohere, Ollama, DeepSeek, Google, Mistral, MiniMax, Moonshot, Nvidia, and llama.cpp, so your application code never changes when you switch models or providers. The Go binary starts on port 8080 and normalizes authentication, streaming protocols, and response formats across all backends transparently. Native Model Context Protocol support auto-discovers tools from connected MCP servers and injects them into LLM requests without client-side management, enabling server-side tool execution across any provider that supports function calling. Agent-to-Agent protocol integration allows distributed agent communication through a declarative Agent Definition Language that generates production-ready Go or Rust servers from a single YAML manifest. The dedicated Kubernetes Operator manages Gateway, Agent, MCP, and Orchestrator custom resources with automatic HPA scaling, OIDC authentication, and service discovery that rebuilds MCP configurations when the discovered server set changes. Prometheus metrics and OpenTelemetry tracing provide full request-level observability across the entire inference pipeline. Middleware controls enable per-request provider selection, model routing, and fallback strategies. Official SDKs in Go, Python, TypeScript, and Rust provide typed client interfaces with streaming support. Docker Compose deployment requires only environment variables for API keys. A CNCF Sandbox applicant. 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.

Scira is an AI search engine that breaks complex research questions into sub-tasks, retrieves grounded answers from live sources, and cites every claim with clickable links to the original evidence. Formerly known as MiniPerplx and now backed by nearly 12,000 GitHub stars, the platform implements agentic research planning where language models decompose queries, select appropriate tools, retrieve information in parallel, and synthesize responses with inline citations. Seventeen distinct search modes cover Web, Academic, Extreme, X (Twitter), Reddit, GitHub, Stocks, Crypto, YouTube, and Prediction markets, each activating a curated subset of the 28 built-in tools. The Extreme mode deploys a deep research agent with multi-step planning, parallel source retrieval, code execution in sandboxed Daytona environments, and R2 artifact storage for generated charts. Model routing spans 50+ AI providers through a unified configuration layer supporting OpenAI, Anthropic, Google, xAI Grok, and custom models, with per-mode model assignment based on task requirements. The web search tool supports Exa, Tavily, and Firecrawl as interchangeable providers via a Strategy pattern. Lookouts schedule recurring research agents on cron schedules that monitor topics, track changes, and email summaries using Upstash QStash for reliable execution. PostgreSQL stores chat history, user preferences, and custom instructions while Redis handles caching and rate limiting. 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.

Sketch a wireframe, get working code: Draw a UI turns hand-drawn layouts into web interfaces. It pairs the open-source tldraw canvas with an OpenAI vision model: you sketch a layout - boxes, labels, buttons, arrows, whatever communicates the idea - select the drawing, and click Make Real. The app snapshots your selection as a PNG, sends it to the vision API with instructions to return a single HTML file styled with Tailwind CSS, and renders the result in an iframe directly on the canvas next to your sketch. The loop is iterative: annotate the generated prototype or redraw parts of it, select both the sketch and the previous result, and generate again - the model receives the earlier HTML as context and produces an updated version. Built by Figma engineer Sawyer Hood as one of the first viral GPT-4 Vision demos and the basis for tldraw's "Make Real", it is a Next.js app that runs against your own OpenAI API key. Self-hosting matters here: the upstream demo ships without authentication, so a private deployment keeps your API key from being drained by strangers. 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.

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.

Audio lectures become structured, Markdown-formatted notes in about a minute with ScribeWizard (also known as GroqNotes). Upload an MP3, WAV, or M4A file - or paste a YouTube link - and the app runs a three-stage pipeline on Groq's LPU inference hardware: Whisper Large v3 transcribes the audio, a larger Llama model drafts a comprehensive outline of the material, and a faster Llama model fills each section with detailed content. This scaffolded prompting strategy is the core idea: the strong model handles structure where quality matters most, the fast model handles volume, and Groq's 1200+ tokens-per-second inference keeps the whole process near real time. Output renders as clean Markdown with support for tables and code blocks, and finished notes download as text or PDF. Model selection is configurable - swap in other Groq-hosted open models like Mixtral or Gemma to trade speed against quality or work around rate limits. Built as a single Streamlit app by Benjamin Klieger at Groq, it needs only a Groq API key to run, making it one of the simplest self-hosted AI tools to operate.

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!

Scrumboy is a Kanban and sprint management tool that ships as a single Go binary backed by SQLite, deploys in under ten seconds via Docker, and uniquely integrates with AI coding agents through a standards-compliant MCP JSON-RPC endpoint. The dual-mode architecture supports Full mode with bootstrapped authentication, TOTP two-factor auth, OIDC/SSO integration through Keycloak, Authentik, Auth0, or Entra ID, role-based access control across Owner, Admin, User system tiers plus per-project Maintainer, Contributor, and Viewer roles, and Anonymous mode that generates instant shareable boards accessible via unique URLs with zero signup requirement. Custom workflows allow user-defined lane configurations per project including designated "Done" lanes, while sprints with configurable one or two-week cycles include board-level sprint filtering and the ability to disable and re-enable sprint tracking without losing history. Real-time Server-Sent Events power instant multi-user board updates, and outbound webhooks deliver JSON payloads to registered URLs when domain events fire with HMAC signature verification. The MCP endpoint at /mcp/rpc enables native integration with Cursor, Claude Code, and other AI agents through OAuth 2.1 with PKCE authorization, while API access tokens support CLI automation and CI/CD pipelines. Additional capabilities include VoiceFlow voice commands, per-project sticky-note walls, Markdown and Mermaid diagram support in task notes, append-only audit trails, VAPID Web Push notifications, SMTP password reset, Trello import, JSON backup with merge/replace/copy strategies, and 22-language internationalization. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. AGPL v3.0 licensed.

Why should your chat history live on someone else's servers? Chatpad AI - a React/TypeScript front end for the OpenAI API, built on the Mantine component library - is designed around that question. Enter your own OpenAI API key and start chatting with GPT models; every conversation, prompt, and setting is stored locally in your browser via DexieJS over IndexedDB, with no tracking, no cookies, and no backend database at all. That architecture is the point - the Docker image is just Nginx serving static files, making it one of the lightest AI deployments in the catalog, and pay-per-token API pricing typically undercuts a ChatGPT Plus subscription for moderate use. The interface earns its "premium quality" tagline with the details: a persona selector that switches communication styles per conversation, a saved-prompts library for messages you reuse constantly, organized chat history, and full data export/import so conversations move between browsers or into backups as files you control. A JSON config file customizes defaults - models, API endpoints, UI options - without rebuilding the image. AGPL-licensed, with desktop builds available upstream. For teams that want ChatGPT's utility with a self-hosted, zero-telemetry footprint, Chatpad is the minimal, sane answer.

Describe what you want in plain language and get real SQL against your real schema: SQL Chat is an open-source, chat-based SQL client from the Bytebase team. Instead of writing queries in a traditional editor, you connect a database and describe what you want in plain language; the AI reads your schema automatically, generates SQL that references real table and column names, executes it, and returns tabular results in the conversation. Follow-up messages refine the query, so exploration becomes a dialogue - narrow a result set, add a join, change an aggregation - without retyping statements. It supports MySQL, PostgreSQL, SQL Server, TiDB Cloud, and OceanBase from one interface, and covers modification as well as reads: insert, update, and delete operations phrased conversationally. Built with Next.js and TypeScript, it deploys as a single stateless Docker container in single-user mode - connection profiles live in the browser, so there is nothing server-side to maintain. A custom AI endpoint setting routes inference through any OpenAI-compatible API, including self-hosted models, and an optional database-backed mode adds accounts and quotas for offering the tool to a team. MIT-licensed.