Doca puts rich text, Markdown, spreadsheets, slides, and an infinite canvas under one login and one permission model, giving individuals and small teams a self-hosted workspace for writing together. Every format supports real-time co-editing with presence, comments, saved history, and manual snapshots, and rich text and Markdown documents can be restored to an earlier version. Documents live in knowledge libraries with tree navigation, invitations, inherited permissions, share links, and trash, while personal files and shared folders sit on local disk or S3-compatible storage. Knowledge books go further: they subscribe to sources, run an editable workflow, keep source evidence, and route results through human review. A personal AI assistant, powered by whichever model you configure, searches authorized documents, reads PDF and Office attachments, edits images, and prepares browser drafts. MCP services let external AI clients such as Codex use those tools under your permissions. Sign in with a password, OIDC, Google, GitHub, WeChat, or QQ, review registrations before they go live, and send webhooks to other systems. A plugin SDK and marketplace add business modules, and a browser extension clips pages into documents. The interface ships in Chinese and English. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

Moltis gives individuals and teams a completely private personal AI agent server that bridges conversational assistants to everyday messaging platforms while executing real-world computing tasks inside secure execution environments. Users can interact with autonomous agents across Telegram, Discord, WhatsApp, Slack, Matrix, and browser interfaces to draft correspondence, automate research, and schedule recurring cron tasks. The system coordinates multi-agent delegation by spinning up specialized sub-agents with dedicated roles for code generation, pull request reviews, quality assurance testing, and technical documentation. Built-in sandboxing isolates tool operations within container boundaries or WebAssembly modules, ensuring shell commands, web scraping routines, and script executions cannot alter underlying operating system files without explicit permission. Native Model Context Protocol integration allows operators to attach external data endpoints, database connectors, and custom command-line utilities without rewriting core routing logic. Persistent memory preserves conversational context and document embeddings across multiple sessions, allowing assistants to recall prior discussions, user preferences, and project guidelines indefinitely. Administrators can configure granular tool approvals, manage WebAuthn passkey authentication, and review real-time WebSocket communication logs through an embedded control panel. 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.

Thirteen-plus LLM providers, one unified client: NextChat (formerly ChatGPT-Next-Web) is an open-source AI chat interface built on Next.js that spans OpenAI GPT-4, Anthropic Claude, Google Gemini, DeepSeek, Groq, Azure endpoints, and self-hosted backends like Ollama, LocalAI, and RWKV-Runner. Its defining trait is minimalism - the first screen loads in about 100 KB, the desktop client is roughly 5 MB, and there is no database or user system to operate; chat history lives locally in the browser with optional WebDAV or UpStash Redis sync. The Mask system saves reusable prompt-template personas you can share and debug, long conversations auto-compress to fit context windows, and Markdown rendering covers LaTeX, Mermaid diagrams, and code highlighting with streaming responses. Plugins add web search and calculators, MCP support enables external tool calling, and Artifacts previews generated content in a separate pane. Ships as a web app, Docker image, and Tauri desktop builds for Windows, macOS, and Linux, translated into 20+ languages. MIT-licensed.

Run Claude Code, Codex, Gemini CLI, OpenCode, and sixteen other AI coding agents from one workspace instead of juggling twenty terminals. Every agent connects through the Agent Client Protocol, so conversations render as structured chats with tool cards, live diffs, and interactive replies rather than raw terminal scrollback. Codeg imports the session history each agent already keeps on disk, making every past conversation searchable and resumable, even when you hand the thread to a different agent. Mention one agent with an @ to delegate work to another, or run several side by side and watch their progress stream into the same conversation. Queued to-dos execute unattended in isolated git worktrees, leaving finished changes ready for your review and approval instead of touching your working tree. An infinite canvas arranges chats, files, terminals, and notes on one board, while git tooling, token usage tracking, and MCP server support stay one panel away. Deployed as a headless server, Codeg answers in any browser and through Telegram, Lark, and WeChat channels, so agent work continues while you are away from your desk. 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.

Rakazo lets you hire AI bots the way you would onboard teammates: each gets a job, persistent memory, its own sandboxed computer, and a schedule, and it reports back in chat while you check in from any device. Start from templates such as Sales Outbound, Inbox Manager, Talent Scout, Expense Manager, Coding Agent, or Chief of Staff, then tune the instructions, tools, and limits until the bot works the way your team works. Every bot can run on a different model, so research uses one provider while coding uses another, and a local model served by Ollama or LM Studio keeps sensitive work off third-party servers. Bots work on real computers with a browser, terminal, file system, and graphical desktop you can watch or take over, choosing shared team computers or isolated private ones. When a task outgrows one bot, it delegates pieces to peer bots or short-lived subagents and folds their results back into its own thread. Voice mode lets you dictate messages and hear spoken replies, while routines run on schedules so follow-ups, reports, and inbox sweeps happen while you are away. You decide which actions need your approval before a bot takes them, and integrations via Composio, Pipedream Connect, MCP servers, and OpenAPI documents connect bots to tools you already use. 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.

LibreDesk unifies live chat, email, and future channel integrations into a single agent inbox where every customer conversation converges regardless of origin, replacing per-seat-priced tools like Zendesk, Intercom, and Freshdesk with a zero-cost alternative that has surpassed 2,000 GitHub stars. Built on a Go backend with a Vue.js 3 and ShadcN UI frontend, it ships as a single binary requiring only PostgreSQL and Redis. The embeddable live chat widget drops onto any website with a snippet, while the AI assistant handles initial customer queries using answers grounded in your knowledge base before escalating to human agents when needed. Agent copilot drafts replies, summarizes conversation threads, and rewrites messages for tone adjustment directly within the inbox interface. Automation rules trigger on conversation events to tag, assign, and route tickets based on configurable conditions, while auto-assignment distributes workload by agent capacity or custom criteria. SLA management tracks response and resolution time targets with breach notifications, and automated CSAT surveys measure satisfaction after conversation closure. Macros save frequently sent responses as reusable templates that simultaneously set tags and assign conversations. Role-based access control provides granular per-action permissions for teams and individual agents, and SSO supports Google, Microsoft, and any OIDC provider. The HTTP/JSON API and webhook system enable custom integrations with external tools. 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.

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.