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.

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.

Your front desk phone rings at midnight and nobody sane is awake; QuickVoice answers it with an AI agent you configured, on servers you own, with call recordings you control. Build agents in the web console: write the prompt, pick speech-to-text, language model, and voice, set the first message, then link a real phone number from Twilio or Telnyx through LiveKit SIP trunks. Inbound callers get a receptionist that answers questions from your uploaded knowledge base, PDFs and web pages chunked and embedded for live retrieval, while outbound mode fires single quick calls or batch campaigns for reminders and follow-ups. Agents can invoke allowlisted MCP tools mid-call, so checking an order status or booking a slot happens inside the conversation instead of after it. Every call lands in the log with transcript, recording, and metadata, searchable from the analytics dashboard, and privacy controls redact personal data by default, can suppress recordings entirely, and sweep old transcripts on a retention schedule. Multi-language voices, per-agent runtime overrides for campaigns, organization accounts with API keys and audit logs, and Stripe billing hooks round out a platform built for teams who would rather inspect their voice stack than rent a black box. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

ScribeCrate is a self-hosted speech-to-text API that turns recordings into transcripts, subtitles, and English translations on your own server. It speaks the OpenAI Whisper API fluently: point any compatible client at your server's address, swap in your API key, and uploads come back as text. Ask for plain text, JSON with timestamps, or ready-to-publish SRT and WebVTT subtitle files, and for long recordings the segments can stream back over SSE as they are decoded. Turn on speaker diarization and every segment is labeled with who is speaking, which makes interview and meeting transcripts readable at a glance. Choose the model that fits the job, from tiny for quick drafts to large-v3 for maximum accuracy, and run it on a modest CPU, a Raspberry Pi class ARM board, or an NVIDIA GPU. Almost any recording works: MP3, M4A, WAV, WebM, OGG, and FLAC are all accepted, and with models cached in advance the server keeps transcribing with no internet connection at all. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT 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.

One clean interface in front of Anthropic, OpenAI, Google Gemini, Cohere, and more: Chat Chat is a Next.js front door to the major AI providers, ending the juggling of separate subscriptions, tabs, and UIs per model. Bring your own API keys, pick a provider and model per conversation, and switch between them as the task demands: Claude for long-form reasoning, GPT for code, Gemini for multimodal work - the interface stays identical. Beyond configured presets, custom providers plug in with their own API endpoints and keys, which covers OpenAI-compatible gateways and local inference servers. The design splits into two dedicated modes: a chat interface for conversational work with customizable system prompts, and a search interface that pairs AI processing with query handling for research-style questions. The stack is modern and hackable - Next.js 14, Tailwind CSS, shadcn/ui on Radix primitives, Jotai for state - with full internationalization including English, Chinese, and Japanese. Self-hosting means your conversation history and API keys live on your instance rather than a third-party wrapper service, and pay-per-token API pricing typically beats stacking multiple monthly chat subscriptions. AGPL-licensed and deliberately simple to deploy: one container, environment variables for keys, done.

RushDB is a database your AI agents can actually understand, because it remembers the shape of everything you write. Send nested JSON and each object becomes a record, automatically linked to its parent, while field names, types, and values are cataloged on every write. Agents introspect that catalog before querying, so they ask questions the data can answer instead of hallucinating tables that never existed. The same records answer five query styles: a JSON query language, SQL over the PostgreSQL wire protocol, Cypher over HTTP or Bolt, Gremlin, and Mongo-style document queries. Vector, full-text, and hybrid search run against the same store, so an agent can find the record that mentions a phrase and the records merely similar to it. Everything ships as one binary with one data directory, speaking HTTP on port 3000, PostgreSQL on 5432, and Bolt on 7687 to the drivers and tools you already use. Point your SDKs, SQL clients, BI tools, or local MCP-connected agents at it, and back it up, replicate it, or restore to a point in time with the engine's own tooling. 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.

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.

With 1,450+ GitHub stars and a live demo on Vercel, this Bloomberg Terminal clone delivers a professional-grade financial dashboard without the $24,000 annual seat license. The Next.js 15 App Router with React 19 and TypeScript serves a single-page terminal interface optimized for constantly mutating financial data, with partial pre-rendering enabling sub-500ms initial loads even on data-heavy views. Upstash Redis caches AlphaVantage market data to minimize API calls while maintaining sub-second update latency through React Query polling with configurable refresh rates. OpenAI integration provides AI-powered market insights, sentiment analysis, and trend interpretation directly within the terminal interface. Multiple specialized views cover market data tables with bid/ask spreads, financial news aggregation with category filtering, market movers highlighting top gainers and losers, and volatility analysis with historical comparison charts. Jotai atoms manage local state for watchlists, layout preferences, and terminal sessions while React Query handles server-state synchronization with aggressive stale-while-revalidate caching. The shadcn/ui component library with Tailwind CSS delivers accessible, keyboard-navigable interface elements styled after Bloomberg's iconic dark terminal aesthetic. Security features include origin restriction, rate limiting via Redis, and Zod-based input validation on all API routes. Motion (formerly Framer Motion) animates transitions between views and data updates without layout shift. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

Amplication turns entity definitions into production-ready backend services, generating NestJS with Prisma and Apollo GraphQL for Node.js or ASP.NET Core for .NET, eliminating months of boilerplate. The plugin-driven Data Service Generator hooks into code generation lifecycle events, enabling teams to inject CI/CD manifests, proprietary authentication schemes, testing configurations, and cloud-specific deployment targets for AWS, Azure, and GCP without forking the core generator. Blueprint templates encode organizational architecture standards, security policies, and coding conventions into reusable foundations that keep every generated service consistent across the engineering organization. Jovu AI translates natural language requests into entities, relationships, fields, modules, DTOs, and custom API actions, automatically aligning each resource with predefined standards. Generated services include full CRUD operations with input validation, Swagger/OpenAPI documentation, authentication middleware, database-agnostic ORM via Prisma, optional React Admin interfaces, and Jest test scaffolding. Code output syncs to Git repositories as pull requests, preserving standard review workflows while letting developers edit every generated line and add custom business logic. Supports PostgreSQL, MySQL, and MongoDB as database targets. Over 16,000 GitHub stars with enterprise adoption. Apache 2.0 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.

Tiledesk lets you build AI-powered conversational agents with a visual drag-and-drop designer, then deploy them simultaneously across web chat, WhatsApp, Telegram, Facebook Messenger, Instagram, email, and Slack without rebuilding per channel. The no-code Design Studio combines LLM-powered conversations with conditional logic, external API calls, and branching dialogue trees that work identically everywhere. Multi-RAG knowledge management separates content into isolated repositories with hybrid search combining traditional full-text retrieval and semantic understanding via Qdrant vector embeddings, enabling accurate answers even when users phrase queries in unexpected ways. LLM integration supports GPT-4, GPT-4o, Anthropic Claude, and any model exposing an OpenAI-compatible API including locally hosted models via Ollama for complete data sovereignty. The human-in-the-loop system provides seamless escalation from AI agents to live support staff with full conversation context preserved, while multi-agent workflows enable complex orchestration where specialized bots collaborate on different aspects of a customer interaction. REST and MQTT APIs power integration with external systems and webhook-triggered automations, and pre-designed templates accelerate common scenarios. Docker Compose deployment starts the full stack including server, dashboard, messaging engine, and widget. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

Xianyu SaaS runs all of your Xianyu (Goofish) shops from one self-hosted console, answering buyers with AI, delivering digital goods the moment orders verify, and keeping every store isolated in its own process. Add each shop by scanning a QR code in the Xianyu app, then switch between stores from one header while the overview tracks messages, replies, delivery results, orders, and pending tasks. The AI customer service center lets you pick a service persona, write shop-wide reply requirements in plain language, and maintain a separate knowledge entry for every product, covering audience, specifications, usage, delivery notes, and after-sales wording. Keyword rules answer the repetitive questions first, with product-specific rules outranking store-wide ones, and anything unmatched falls through to the AI with product knowledge and chat history in context. When a buyer pays, the system re-checks the platform order before delivering, drawing card keys one to fifty at a time from named pools, sending netdisk resources, or posting fixed text instructions, with a five-minute sweep catching orders missed while a shop was offline. A conversation workbench lets you search chats, take over from the AI with one click, send up to eight queued images, and jump from any order straight into the buyer's thread. A built-in operations agent manages a shop through chat, updating product knowledge, toggling reply rules, or binding delivery stock on request. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. GPL-3.0 licensed.

Describe the small app you keep wishing existed, and Tinykit builds it, gives it a database, and puts it live on your server. Tell it the tool you need and the agent writes the code, creates the data collections behind it, and wires the two together, then steps aside. The result is not a screenshot of an app; it is the app, served from your own server with its data syncing in real time and its files stored beside it. Open the built-in code editor to adjust the single file behind each app, or avoid code entirely: content fields let you edit text like a miniature CMS, and the design system panel restyles colors, fonts, and shadows visually. Every change takes a snapshot, so bold prompts carry an undo button and nothing is one bad idea away from lost. Hosts running errands for a household, an internal team, or a portfolio of side projects can keep adding apps, each reachable on its own domain, with token costs for every prompt shown in real money so the building budget is never a mystery. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

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.

Whirl puts every top AI model in a single conversation and remembers what you were working on last week, so you can switch models mid-thought without losing the thread. Ask for a report, a chart, or a small interactive page and it appears as a living artifact in a side panel, still editable while you keep chatting, and shareable by link when it is ready to leave the conversation. Connect your own tools over MCP, with OAuth sign-in handled for you, or install skills that teach the app new tricks your team relies on. Long-term memory carries your preferences and project context from chat to chat, and live web search with page reading grounds answers in today's pages instead of the model's training data. Sensitive threads can be locked with a password that encrypts them on your device, where the server never sees the key and only zero-retention models may answer. Around those headline pieces sits the everyday kit: incognito mode, a message queue for when you think faster than the model replies, voice input, image generation, file attachments, folders, and sharing controls. An admin console manages the model catalog, integrations, and skills, and the interface itself switches between light and dark with your choice of accent color, installable as a mobile web app. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

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.

Cortex Hub gives every AI coding agent your team runs a shared brain, so what one agent learns in a repository is still there when the next agent, or the next person, opens it. Starting a session recalls the team knowledge and your own memory for that project, shows who else is editing, and picks up any task waiting for you. Agents search code by meaning and structure rather than text strings, tracing symbols, callers, and the blast radius of a change before touching it. Findings, file risks, and hard-won lessons are stored against the files they belong to, so they resurface exactly where they matter. Ending a session runs build, type, and lint checks, reports the result, and leaves a summary the next session starts from. A conductor can hand tasks to worker agents on other machines and track them centrally, while the dashboard shows sessions, keys, usage, and token savings across the team. Embeddings run locally by default, so your code memory never leaves the building just to be searchable. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.