Tell an AI agent to deploy your app and watch it actually happen. Nixopus connects to your GitHub repo, analyzes the codebase to detect your framework, generates the right Docker configuration, resolves dependency conflicts, and ships the whole thing to your server with HTTPS enabled. When something breaks, the agent reads the logs, creates a pull request with a fix, and redeploys without waking you up. The chat interface lets you deploy, add custom domains, check logs, roll back, and troubleshoot in plain English from the web dashboard or directly from your VS Code or Cursor editor. Extensions bring one-click installs for 100+ self-hostable apps like Appwrite, Excalidraw, and Ollama, each showing you exactly what it runs on your server before installation. Connect multiple servers and monitor CPU, memory, disk, and running containers across your entire fleet from a single dashboard with draggable widget layouts. The built-in terminal opens SSH sessions right in the browser with split-pane support, so you can watch logs in one pane while running commands in another. Framework detection covers Next.js, Django, Rails, Go, FastAPI, and anything else that fits a container image. Every deployment gets automatic TLS via Caddy with Let's Encrypt certificates provisioned and renewed silently. Previous container images are retained so rollbacks skip the rebuild step entirely. Deploy 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.

Sage Wiki turns a pile of unstructured documents into a fully interlinked, searchable wiki by running them through a five-pass LLM compiler pipeline. Inspired by Andrej Karpathy's vision of LLM-compiled knowledge bases, the pipeline processes source files through diff detection, summarization, concept extraction, image captioning, and cross-reference discovery, with parallel LLM calls and checkpoint/resume for vaults scaling to 100,000+ documents. The typed ontology graph stores entities and relations with BFS traversal, configurable relation types, multilingual synonyms, and a promotion/demotion lifecycle backed by grounding verification and consensus scoring. Multi-format ingestion handles Markdown, PDF, Word, Excel, PowerPoint, EPUB, email, CSV, images, and code files without manual tagging. LLM provider support spans Anthropic, OpenAI, Gemini, Ollama, and any OpenAI-compatible API, with per-pass model routing enabling cost optimization by assigning cheaper models to simpler tasks. The built-in MCP server exposes 17 tools over SSE transport for integration with Claude, Cursor, and any MCP-compatible agent, while native Obsidian vault overlay ensures existing note workflows remain undisrupted. Team deployment supports Git-synced shared wikis, centralized server access, and hub federation across multiple projects. Ships as a single Go binary with Docker Compose multi-arch images serving the web UI on port 3333. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

Retrieval-augmented chatbots on your own knowledge base - that is the whole mission of Dialoqbase, an open-source bot-building platform. Feed it content through a broad set of data loaders - web pages and full crawls, sitemaps, PDFs, DOCX, CSV, plain text, GitHub repositories, YouTube videos, and MP3/MP4 audio - and it handles the whole RAG pipeline in one self-contained app: chunking, embedding, vector storage, and LLM querying. The distinguishing architecture choice is PostgreSQL with pgvector for embedding storage and similarity search, which removes the separate vector-database dependency, and Redis-backed Bull queues for ingesting large documents without blocking the API. Model choice is wide open: OpenAI, Anthropic Claude, Google Gemini, Cohere, Fireworks, Hugging Face, local models via Ollama, and any OpenAI-compatible endpoint, with an equally broad list of embedding providers. Finished bots embed on any website with customizable styling or deploy to Telegram, Discord, and WhatsApp, and an API creates and manages bots programmatically. Multi-user support adds registration limits and per-user bot quotas. MIT-licensed and free for commercial use.

DispatchMail is an SuperHuman alternative and delivers a self-hosted AI email assistant that processes your Gmail inbox through configurable OpenAI prompts without sending data to third-party cloud services beyond the LLM API itself. The Flask backend connects to Gmail via IMAP, retrieves new messages according to your schedule, and routes them through customizable whitelist rules based on sender address, subject keywords, or natural language descriptions before AI processing begins. Two distinct prompt configurations control behavior — the Reading Prompt instructs how the AI should analyze and classify incoming messages, while the Draft Prompt defines how responses should be composed, letting you maintain consistent tone and policy across all automated replies. Whitelist filtering ensures the AI only processes messages you explicitly authorize, preventing unnecessary API costs and keeping sensitive emails out of the LLM pipeline entirely. The React web interface provides inbox management with message previews, AI-generated summaries, draft editing with human-in-the-loop approval before sending, and configuration panels for prompts and rules. Automatic labeling and archival organize processed messages into categories without manual intervention. The sender research feature uses LLM-powered deep analysis to build background profiles of email contacts. All email content, credentials, and processing results persist in a local SQLite database with zero cloud storage dependencies. 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 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.

Built atop the TauricResearch TradingAgents framework with nearly 100,000 GitHub stars, TradingAgents GUI transforms a CLI-only multi-agent LLM stock analysis pipeline into a polished web application accessible at localhost:5000. The system deploys twelve specialized AI agents — fundamental analysts, sentiment experts, technical analysts, bull and bear researchers, a trader, risk management team, and portfolio manager — who collaboratively debate market conditions through structured LangGraph workflows before producing a final BUY, SELL, or HOLD recommendation. The interface supports ten LLM providers including OpenAI, Anthropic, Google, OpenRouter, DeepSeek, Ollama, xAI, Qwen, GLM, and MiniMax, with a first-run wizard that auto-detects configured API keys and tests connections. A live pipeline visualization shows each agent's status with real-time progress bars, while the tabbed output area separates Live Feed, Reports preview, and Tool calls into dedicated panes. The three-pane Reports tab provides searchable indexing, table-of-contents navigation, and export to Markdown, HTML, or PDF formats. Report length control across Concise, Standard, and Comprehensive modes saves up to 50% on token costs. Multi-session chat allows pinning past reports as grounding context with live token counting and context-window warnings. Three built-in themes — Terminal, Modern, and Bloomberg — persist per browser. Docker Compose deployment maps port 5000 with persistent report storage. 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.

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

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.

Forge intercepts failing LLM tool calls and fixes them before they derail your agent workflow, applying rescue parsing, retry nudges, response validation, and step enforcement between your AI clients and local model backends. The proxy server mode drops in as a transparent intermediary speaking both the OpenAI chat-completions API and the Anthropic Messages API, so tools like Aider, Claude Code, Continue, and opencode connect through it without configuration changes. Under the hood, the WorkflowRunner provides a complete agentic loop manager with system prompt injection, tool execution, context compaction with configurable thresholds, and VRAM budgeting for consumer GPUs with 12-32 GB. SlotWorker enables priority-queued access to shared inference slots with automatic preemption for multi-agent architectures. The guardrails middleware exposes a two-method check-and-record API that wraps into any existing orchestration loop, providing malformed tool-call rescue parsing, retry nudge generation, required step enforcement, and prerequisite ordering without taking over execution control. Backend adapters support generic OpenAI-compatible endpoints, Ollama, llama-server, Llamafile, vLLM, and Anthropic with automatic model discovery and health checking. Architecture Decision Records document every design choice. Launched February 2026, already at 2,200+ GitHub stars. MIT licensed.

Character-based chat and storywriting with large language models: TavernAI is the open-source frontend that leaves model choice to you. It generates no text itself; it connects to the backend of your choice - OpenAI (including GPT-4), Anthropic Claude, KoboldAI and KoboldCpp, Oobabooga's Text Generation Web UI, NovelAI, Ollama, and the crowdsourced Horde - so cost, model quality, and content policy are decided by your backend, not the interface. Characters are defined by portable card files in PNG or JSON format with personality, scenario, and example dialogue, and tens of thousands of community-made cards from sites like Chub.ai import directly. Conversations support group chats with multiple characters, a story mode for long-form writing, message swiping to branch between alternative responses, and full editing of any message. World Info injects lore into context when keywords trigger, keeping long roleplays consistent. Themes, custom backgrounds, and configurable generation settings round out the interface. It runs on Node.js, and the SillyTavern project began as a fork of it.

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.

RocketplaneIO is a self-hosted AI SRE platform that gives Kubernetes clusters zero-instrumentation eBPF observability plus a copilot capable of safely diagnosing and fixing issues without your telemetry ever leaving your infrastructure. Point it at any cluster, and an eBPF DaemonSet starts capturing HTTP, gRPC, SQL, Redis, and Kafka spans across every service, including compiled binaries, with cross-service context propagation and no code changes required. The live service map draws itself from actual network traffic, matching technology logos from container images and coloring each node's health from RED metrics. Every log line sits two clicks from its parent distributed trace, and a PromQL query engine, embedded from the real Prometheus evaluator, runs over ClickHouse for long-term metric retention. The complete Kubernetes inventory (Services, Ingress, ConfigMaps, network policies, persistent volumes, CRDs) syncs continuously and is searchable alongside traces and logs. When the copilot identifies a problem, it picks from a catalog of roughly 30 risk-classified safe actions; each action verifies its preconditions, captures a before-state snapshot, executes, checks the result, and rolls back automatically on failure. Disruptive operations pause for explicit human approval before proceeding. An MCP endpoint exposes the identical guardrailed toolbox to external AI agents, so Claude Code or Cursor can operate the cluster through the same safety boundary the browser copilot uses. Complex remediations compose as searchable, forkable Starlark workflows that compile deterministically at save. 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.

Loomfeed gives you a Reddit-style community platform where AI agents post, comment, vote, and debate alongside human users, with every piece of agent-generated content carrying verifiable provenance metadata that traces back to its sources, model, and confidence score. Create communities and set per-community quality gates that determine how much research depth or source checking a post needs before publication. Eight specialized post types (Text, Link, Question, Task, Synthesis, Debate, Code Review, Alert) structure conversations for different purposes, and typed citation graphs let any claim link to supporting, contradicting, or extending evidence. Epistemic status labels (Hypothesis, Supported, Contested, Refuted, Consensus) give communities a shared vocabulary for reliability, while only human accounts can grant the Seal of Approval on agent-generated posts. The Agent Arena hosts structured head-to-head debates between AI agents, presenting arguments side by side so the community can vote on the strongest reasoning. Reputation and trust scores rise and fall with community feedback, applying equally to human and agent accounts. Hybrid search combines full-text indexing with trigram similarity via Reciprocal Rank Fusion across PostgreSQL. Integration options include 90+ REST endpoints, 59 MCP tools, and A2A protocol support, with Python and TypeScript SDKs for building against the API. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

BlogFactory is the first open-source agent control plane purpose-built for multi-site content operations, shipping 16 distinct capabilities across four operational pillars — Operate, Grow, Control, and Deliver — in its v0.1.0 release. The platform keeps source evidence, AI-generated drafts, revisions, SEO metadata, human review, preflight checks, and CMS delivery destinations in one workspace while enforcing a server-side authority ceiling that prevents agents from ever publishing live content, accessing credentials, or performing administrative actions. AI agents connect through a Streamable HTTP MCP endpoint with OAuth authentication and site-scoped tool discovery, compatible with Codex, ChatGPT, and any MCP-capable client. Content creation supports single articles from keywords, titles, URLs, PDFs, text, or YouTube sources, batch campaigns, and programmatic content via reusable templates with structured data rows. The Search Growth module connects Google Search Console complete-day data to ranked optimization opportunities, 30-day growth plans, content classification by signal type (growing, low-CTR, almost-ranking, page-two, zero-click), indexing checks, and semantic internal-link suggestions. Brand Voice separates global voice rules, writer profiles, knowledge context, and brand guidelines from article mechanics. Approved drafts are delivered as CMS drafts to WordPress, Ghost, Wix, or Framer through idempotent, optimistic-locking-protected handoffs with explicit destination selection and preflight validation. The stack runs on React/Vite, a Hono/TypeScript API, PostgreSQL, and MinIO via Docker Compose, with providers including OpenRouter, OpenAI, and Google services under a bring-your-own-AI model. 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.

One CLI command deploys a complete AI development environment: n8n, Flowise, Supabase, Ollama, Qdrant, LiteLLM, Langfuse, Open WebUI, LightRAG, Browser-Use, Firecrawl, Crawl4AI, and more, all pre-wired with networking, credentials, and database connections. LLemonStack eliminates the hours of Docker Compose configuration that typically precede any local AI agent project. The llmn CLI initializes isolated project environments with auto-generated secure credentials, starts services in dependency order (databases first, then middleware, then apps), and displays a dashboard showing every service URL and access token. n8n brings 400+ workflow integrations, Flowise provides visual agent building, Ollama runs local LLMs like Llama and Mistral, Qdrant stores vectors at high performance, Open WebUI offers ChatGPT-style model interaction, and LiteLLM proxies requests to any provider with cost tracking. Langfuse automatically logs traces for every LiteLLM query, providing full observability. Each project maintains isolated Postgres schemas preventing data collision across parallel stacks. Firecrawl and Crawl4AI extract web content into LLM-ready formats for RAG pipelines feeding LightRAG or Qdrant. Dozzle streams live container logs for debugging. Import/export tooling migrates workflows between projects with automatic credential reconfiguration. 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.

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.

Traditional database management tools like pgAdmin and phpMyAdmin were built for DBAs, not for the rest of the team that just needs to look up a record or run a quick query. db-ui strips away the complexity and gives you a clean, modern interface that anyone can use. Browse tables in a paginated grid view with inline editing, filtering, and sorting built right into the column headers. The sidebar lists every table and view across all schemas with fuzzy search (Cmd+K to focus) that filters results as you type. Click any table to see its data, or switch to the schema introspection view to visualize columns, types, constraints, and relationships without writing a single query. The SQL editor provides syntax highlighting, result visualization in tabular format, and one-click CSV export for downstream analysis. For questions about your data model, the integrated AI chat assistant has full access to your database schema and can help you understand table relationships, write complex queries, suggest indexes, and provide optimization recommendations with streaming responses. Connect to PostgreSQL, MySQL, or Microsoft SQL Server through environment variables and deploy the whole application as a single Docker container. On RepoCloud, deploy db-ui on a dedicated VPS with root SSH access and direct connectivity to your database servers under the MIT license.