A self-hosted "second brain": Khoj indexes your own files and answers questions from them, parsing Markdown (whole Obsidian vaults included), org-mode, PDF, Word, plain text, Notion pages, GitHub repositories, and images described by a vision model, then embedding everything with sentence-transformers into a vector index for semantic search and RAG with cited sources. Any LLM backend works: local models like Llama, Qwen, or Mistral via Ollama, or cloud models like GPT, Claude, and Gemini. You can build custom agents, each with its own persona, scoped knowledge base, chat model, and tools such as web search and code execution. Scheduled automations run recurring research and deliver newsletters or notifications to your inbox, and research mode performs multi-hop web searches with inline citations. Access it from a browser, the Obsidian plugin, Emacs, desktop, or WhatsApp - all clients connect to the same self-hosted instance, making Khoj one of the few AI assistants Emacs users can point at decades of org files. Semantic search means recall works without exact keywords: "that paper about forecasting with transformers" surfaces the right PDF even when you cannot remember its title. Switching LLM backends never requires re-indexing your documents, and with a local model via Ollama, even inference stays on hardware you control - journals, research, and private notes are never sent anywhere. Python/FastAPI stack, AGPL-licensed, with PostgreSQL storage.

Bridging local hardware and cloud intelligence, OwnPilot orchestrates autonomous multi-channel agent swarms and visual workflow pipelines while keeping sensitive personal records strictly on private infrastructure. Users can trigger autonomous task runs that browse websites using headless browser automation, extract data tables, and summarize research directly into encrypted markdown notebooks. The built-in workflow canvas allows individuals to construct branching automation sequences combining large language models, conditional logic gates, iterative data loops, and human-in-the-loop approvals. Users delegate calendar scheduling, task tracking, expense budgeting, and contact lookups through conversational chats conducted over web portals, Telegram bots, or WhatsApp numbers. Operators can dispatch coding agents to inspect local repositories, execute shell commands in sandboxed environments, and stream live terminal logs as automated patches develop. The platform also enables home automation enthusiasts to monitor MQTT telemetric feeds from microcontrollers, queue device commands, and receive instant alert notifications when sensor thresholds trigger. Advanced security layers inspect all incoming prompts for personal data patterns, enforce strict permission boundaries across file directories, and generate tamper-evident audit logs for every autonomous tool call. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

Every AI agent gets a face, a colour, and a job in Murmur, a chat app that makes running Hermes Agent as friendly as texting a colleague. Start from a template (Researcher, Writer, Planner, Coder, Coach, or Chef) or describe a new agent from scratch, then talk to one at a time or drop several into a group room and call on a single one with an at-mention. Replies stream in live, long jobs show a plan that ticks itself off, and every step appears in plain words. Connect a model with a ChatGPT plan, a local model server, or an API key from OpenRouter, OpenAI, Anthropic, and others, with the model and thinking effort chosen per agent or chat. Agents can reach Notion, Linear, Todoist, Figma, and dozens of other apps, and they ask for an Allow or Don't allow before changing anything important. Morning briefings run as routines, a memory view shows what each agent knows with controls to edit or forget it, and WhatsApp or Telegram can be linked by scanning a code. A voice call mode lets an agent answer out loud, and slash commands set long-running goals or ask quick side questions. Chats sync across browser, desktop, and phone. Solo builders, homelab fans, and small teams get a calm front door to their own agents. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

Ask for a recycling reminder from your phone on Sunday and have a research report waiting by Monday, without handing your data to a subscription service. PocketPaw is a personal agent you host yourself, reachable from the browser dashboard or the chat apps you already use, including Discord, Slack, WhatsApp, Telegram, Signal, Matrix, Teams, and Google Chat. Pick a backend for the work: Claude Agent SDK, OpenAI Agents, Google ADK, Codex CLI, OpenCode, or Copilot SDK, then point it at a cloud key or a local Ollama model. Over fifty tools cover browsing, web search, files, shell commands, OCR, voice, image generation, and delegation to helper agents. Reminders and scheduled intentions run on their own, and memory keeps long-term facts and compacts old sessions. Identity files shape the agent's tone and instructions, and a skills library adds new slash commands. A guardian model reviews tool calls, with injection scanning, plan mode approvals, tool profiles, and an audit log for oversight. Analytics show cost, latency, and traces against monthly budget caps. Memory, tool logs, and cost traces all live on your own server. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

Picture a small staff of AI agents clocking in on your own server, each with a name, a specialty, its own model, and a private Linux desktop it can click around in. Every agent works inside a disposable Docker workstation with a shell, persistent files, and a Chromium browser, so it can research the web, write and run code, and finish multi-step tasks without touching your own files. You watch an agent click and type in real time, and when a login, payment, or one-time code needs a human, you take over the desktop, then hand it back with a note and let it continue. Pair a Telegram bot by scanning a QR code and you can assign work, answer questions, and receive results from your phone, with no public URL or port forwarding. Routines turn recurring requests into schedules, so a morning briefing, a price watch, or a weekly report runs by itself and reports back when it is done. Each agent can use a different model, from OpenAI, Anthropic, Google, xAI, Groq, Mistral, or DeepSeek to a local Ollama endpoint, and every reply shows its cost while a monthly budget pauses paid models automatically. Agents remember what matters about you across every thread, and logins or cards you save sit in an encrypted vault the agents themselves never see. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

Nod is a personal AI assistant with its own computer, so you can hand it an errand like chasing an unpaid invoice or cancelling a trial and watch it finish the job on real websites. One ongoing conversation follows you from the browser to Telegram and WhatsApp, and long jobs become saved tasks with live status lines on a Scheduled page. Connect Gmail, Calendar, Slack, Notion, Linear, or an n8n instance, and it reads threads, drafts the replies you owe, and prepares a one-page brief before each call. Every action that could change something is checked against your rules, and anything uncovered waits for your yes. Passwords, codes, and cards sit in a Vault that the server types into websites, so the model never sees them. Memory notes are visible, editable, and tied to the message they came from. Schedules run recurring checks like a weekly recap or a price watch that speaks up only on change. Usage lists every action with costs and a monthly spending limit. Pick OpenAI, Anthropic, Gemini, OpenRouter, Bedrock, or a local Ollama server as the model. 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.

Mail, chats, tickets, alerts, and reports stop being five inboxes to check and become one sorted rail in Taskuary, your self-hosted AI work partner. A triage pass reads each arrival and gives it one verdict: nothing to do, a sentence settles it, an agent should work it, talk it through, or it is yours. The rail groups what survives into Urgent, On you, Goals, Agents working, For later, Reports, Advisor ideas, and FYI, and a morning card recaps what changed overnight, what was learned, and today's meetings. The Assistant can walk you through the pile one task at a time, presenting each card with Next, Write reply, Send to agent, and Mark done actions. Coding jobs go to the CLI you already run (Claude Code, Codex, Gemini, Cursor, Copilot, Qwen Code, OpenCode, or Kimi Code) inside your checkout; general jobs open a conversation instead. Results return as drafts attached to the task, and nothing leaves until you approve: replies, comments, invoices, and posts all wait for your click. Disagreeing with a verdict teaches the triage, and learned memory carries your preferences into the next decision. 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.

Your Gmail, Google Workspace, or Outlook inbox, worked by an AI assistant: Inbox Zero sits on top of the account you already have. Its core idea is rules written in plain English - tell the assistant "label invoices and file the PDF to Drive" or "archive cold outreach unless they mention my company" - and it executes against every incoming message. Emails that need a response arrive with a pre-drafted reply written in your tone, learned from your email history and calendar context. Reply Zero tracks what you owe responses to and what you're waiting on; the Bulk Unsubscriber surfaces newsletters you never read (with read-rate analytics) for one-click unsubscribe-and-archive; the Cold Email Blocker auto-archives unsolicited pitches based on your own definition of "cold." Smart Filing routes attachments - receipts, contracts, PDFs - into the right Google Drive or OneDrive folder, and Slack/Telegram integration lets you read, draft, and triage without opening a mail client. Email analytics show top senders and volume trends. It is not a new email client: everything happens in your real mailbox using native filters. Self-hosting means your mail content and the LLM calls that process it run on infrastructure you control.

The meeting ends and, instead of a raw transcript, you get minutes you can file: MeetDo is an open-source meeting-to-action system that hosts the meeting, captions it locally, and finishes the record for you. Start a browser meeting with video, screen sharing, and chat, and watch captions stream from a speech model running on the same infrastructure, so no audio is sent to a cloud note-taker. When the call ends, the transcript becomes structured minutes: summary, agenda flow, conclusions, and action items with owners, instead of a wall of raw text. Five meeting types, from management reviews and project weeklies to interviews and customer calls, shape the record, and custom templates export to DOCX or PDF with your original layout preserved. Domain vocabulary is corrected after recognition, so names, units, and industry terms survive transcription instead of turning into near-miss words. Past meetings stay searchable in a local history, and questions can be asked across them without anything leaving the machine. Editable transcripts let a human fix the record before it is filed, and the whole pipeline works offline after the first model download. 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.

Speakr transforms audio recordings into organized, searchable, AI-enhanced notes with speaker recognition that identifies who said what across your entire recording library. The Python/Flask backend with Vue.js 3 and Tailwind CSS frontend deploys via Docker on port 8899, offering multiple transcription engines through auto-detected connectors: WhisperX for local processing with speaker diarization and voice embeddings, OpenAI Whisper and GPT-4o-transcribe, Mistral Voxtral for cloud diarization, AssemblyAI for multi-hour files, and any custom ASR webservice. Speaker voice profiles use embedding comparison to recognize individuals across different recordings automatically, while custom vocabulary biases the transcriber toward domain-specific jargon. The AI layer goes well beyond transcription: customizable summaries with per-recording, per-tag, and per-folder prompt templates; event extraction surfacing action items and calendar events; per-recording chat with streaming responses; and Inquire Mode for semantic search and natural-language queries across your entire library simultaneously. Smart tags execute custom AI prompts on transcripts for automatic categorization. The REST API with Swagger documentation supports signed webhooks integrating with n8n, Zapier, and Make. Auto-export pushes to Obsidian and Logseq, auto-processing watches directories, and the installable PWA provides mobile-first, offline-capable access with share-target support. 3,600+ stars since May 2025. 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.

Nojoin takes notes on your Meet, Teams, and Zoom calls without sending a bot into the meeting: it records from your browser and transcribes on your own server. Nothing extra joins the call and nothing announces itself to the room; you meet as usual, press record, and the browser captures the audio. Transcription runs locally with Whisper or Parakeet, so the audio never leaves your hardware, and speaker recognition matches voiceprints across calls, so a person you name once is labelled correctly in later meetings too. AI notes can come from an API provider, your existing Claude or ChatGPT subscription, or Ollama on the same machine for fully local processing. During the call, Meeting Edge suggests questions, flags points you may have missed, and explains unfamiliar terms in real time. Afterward, analytics measured from the audio report talk-time share, turn-taking, and overlapping speech. A built-in MCP server hands Claude or ChatGPT 32 tools over your library, 19 of them writable, so an assistant can search every meeting, correct a misheard line, turn action items into tasks, and reconcile attendees with your CRM. Google and Outlook calendars sync automatically, every meeting carries its own chat, and finished notes export to PDF, Word, or plain text. Stored credentials are encrypted with a key you control, and anonymous telemetry can be switched off entirely. 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.

Take the tool sales teams use to never forget a client detail and point it at the people who actually matter - friends, family, the colleague whose kid's name you keep blanking on: Monica is a personal CRM. It's a Laravel/PHP application over MySQL where each contact accumulates the texture of a real relationship: how you met, family members and pets, work changes, addresses, notes from conversations, activities done together, gift ideas and gifts given, even debts owed in multiple currencies. Two features set it apart from every contact app. Reminders with staying power: set per-contact intervals (weekly through yearly), get notified at 30 days, 7 days, and day-of, with automatic birthday reminders and CalDAV sync to your calendar. And a journal linked to contacts: write about dinner with friends, tag each person, and build a timeline that's part diary, part relationship log - plus a daily "how was your day" rating. Monica is deliberately manual and deliberately private: no social network features, no AI, no email scraping, no ads, no analytics - a quiet database of what you know about people you love, on your own server. Multiple vaults and users, labels, custom activity types, and document/photo uploads round it out. AGPL-licensed.

PingCRM is a personal relationship manager that watches your conversations across Gmail, Telegram, Twitter/X, LinkedIn, and WhatsApp and tells you who you are about to lose touch with. Connect those accounts, and every email, DM, mention, and thread lands on one chronological timeline for each person you know. Each relationship carries a transparent score built from reciprocity, recency, frequency, and breadth, so the dashboard can point at exactly who is going cold and show its working. When someone changes jobs, updates a bio, or hits a birthday, life event detection surfaces it while it is still a good reason to write. The same person hiding behind a work email, a handle, and a profile gets merged into one contact through identity resolution, and the suggestion inbox drafts a contextual follow-up for your review, never sending anything on its own. Browse contacts on a map, watch organizations and their people together, filter a notification feed down to what you missed, and ask questions of the whole graph through the built-in MCP server from your AI client. 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.

CRM mechanics applied to your actual relationships instead of a sales pipeline: Nametag is a Personal Relationship Manager (PRM). It exists to fix the things you keep forgetting: when you last talked to an old friend, their kids' names, the birthday you missed twice. Contacts are tracked with flexible attributes - names, birthdays, important dates, and free-form notes for everything else - and organized into custom groups. Where it goes beyond a contacts app is relationship mapping: you define how people connect to each other (family, friends, colleagues, or custom relationship types), and an interactive D3.js-powered graph renders your entire personal network so you can see clusters and connections at a glance. Staying in touch is automated: scheduled reminders fire for birthdays, important dates, and reach-out nudges, with optional email delivery via a Resend API key for password resets and reminder notifications. Built with Next.js, it is mobile-responsive, ships with full dark mode, and supports multiple languages including English and Spanish. Because it is self-hosted, there are no account tiers or contact limits - unlimited people and relationships, with every note about your personal life stored on your own server rather than a social-graph company's cloud. A lightweight, single-container deployment makes it one of the easiest personal tools to run.

Save a link, a PDF, a YouTube video, or a bookmark export to Kompl and it reads the material on arrival, then writes it into cross-linked wiki pages instead of leaving it in a folder you never reopen. Save more on the same subject and the existing pages are rewritten, so source number fifty improves the pages it touches. Every claim carries a numbered citation back to the original text, and when two sources disagree the page records both sides with a confirm or dismiss button. A knowledge graph shows how topics connect, each link backed by the sentence that states it. An onboarding wizard stages pasted text, URLs, uploaded files, browser bookmarks, Twitter exports, Apple Notes, and Upnote exports for review before anything is compiled. Settings pick the compile model from DeepSeek or Gemini, cap daily spend, and show wiki health. Eight MCP tools let Claude Code, Cursor, Codex, and other agents search, read, and cite pages. Full backups export as one zip that restores without further model calls. 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.

Hatchdoor gives your Markdown notes two front doors at once: a fast web interface for you, and an MCP endpoint where AI agents read and edit the very same vault. Point it at any folder of Markdown files, an existing Obsidian vault included, and it indexes everything into a disposable SQLite read model that rebuilds itself from your files if deleted. In the browser you browse folders, follow wikilinks that survive renames, explore backlinks and graph views, and search by keyword or meaning across every vault you mount. The live editor shows Markdown syntax only on the line you are editing and saves automatically, while concurrency checks refuse a save when the note changed underneath you. Agents connect with their own token and start read-only; turn writes on and Claude Code, Codex, Cursor, or Hermes can create, edit, move, and link notes through the same checked operations the interface uses. Saved queries in Obsidian's Bases syntax render as live tables, attachments preview inline, and optional git integration commits and pushes every change back to your vault's repository. 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.

Your team's group chat could have a colleague who has read every email, ticket, and document, remembers all of it, and answers in seconds; MindRoom puts AI agents like that into your chat rooms as full participants. Each agent is a real user on the open Matrix protocol, so you talk to it in MindRoom Chat on web or mobile, in any other Matrix client, or through bridges in Slack, Telegram, WhatsApp, and Discord. Give every agent its own model: a local model for private rooms, a frontier model for hard coding problems, and switch per room or thread whenever the work changes. Agents connect to more than 100 tools, including Gmail, calendars, GitHub, Google Drive, Home Assistant, and any MCP server, and they search your own documents and knowledge bases for answers with sources. Memory persists across conversations and platforms, so an agent remembers people, preferences, and project context months later and can turn repeated work into reusable skills. Before an agent sends an email or runs a command, an approval card shows exactly what will happen; you tap once to allow it, and sandboxed workers keep executed code away from your credentials. Schedule morning briefings, silent inbox checks, and recurring digests in plain language, or wake an agent from any other system with a single HTTP request. 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.

Suparagent turns a single server into a workspace of named AI coworkers that each have a job, a memory, and a folder of their own. Chat with an agent in the browser, pick an engine per conversation, and watch replies stream in as the sidebar keeps every thread searchable. Approval modes decide how much freedom an agent gets: ask first, accept edits, or plan only, so nothing touches a file or runs a command without your say. Routines send a prompt to an agent on chosen weekdays, through a webhook, or on demand, and every run lands in its own conversation. A kanban board with month, week, and upcoming views tracks tasks by owner and priority, and a canvas builds multi-step workflows from schedule triggers, model steps, agent steps, conditions, and approvals. Agents save notes you can edit, delegate to specialists in shared rooms, and reuse saved skills and templates. A usage panel totals turns and tokens by conversation, engine, and day, with a CSV export. Invite teammates with a one-time link, pair a phone, and keep agents working when your laptop is closed. 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.