A personal AI assistant that remembers what it learns and reaches you wherever you are — OpenClaw is an open-source agent gateway built by the OpenClaw Foundation with 247,000+ GitHub stars. It connects to 200+ LLM models through providers like Anthropic, OpenRouter, and OpenAI, and meets you on 21+ messaging channels: Telegram, Slack, Discord, WhatsApp, Signal, iMessage, Matrix, and more. Persistent memory with full-text search lets the agent recall context across sessions, and a self-improving skills system means it gets more capable the longer it runs. Voice wake words and talk mode enable hands-free interaction on macOS, iOS, and Android. A live canvas provides an agent-driven visual workspace. Built-in browser automation, cron scheduling for unattended tasks, and subagent spawning for parallel workstreams round out the toolset. The gateway architecture keeps all sessions, credentials, and conversation history on your own server — nothing transits a third-party cloud unless you choose to connect one. The API key you provide for your chosen LLM provider powers the underlying calls; billing goes through your own account. Running on a dedicated VPS with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

OpenRouter's most-used application by token volume — over 17 trillion tokens processed — Hermes Agent is an open-source autonomous agent built by Nous Research that lives on your server and gets more capable every day. Define a goal in natural language and Hermes plans sub-tasks, executes them through tool integrations, observes results, handles errors, and refines until the job is done or it genuinely needs your input. Persistent memory with full-text search and LLM summarization lets it recall context across sessions, and an agent-created skills system self-improves after complex tasks. A messaging gateway connects Telegram, Discord, Slack, WhatsApp, Signal, and 16 more platforms with cross-channel conversation continuity. A built-in cron scheduler runs daily reports, nightly backups, and weekly audits unattended. Subagent spawning parallelizes workstreams, and six terminal backends — local, Docker, SSH, Singularity, Modal, and Daytona — fit any infrastructure. Works with any LLM provider: Nous Portal, OpenRouter for 400+ models from 70+ providers, OpenAI, Anthropic, or your own endpoint. The API key you supply powers all LLM calls; billing goes through your own account. Running on a dedicated VPS with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

ZeroClaw puts one personal AI agent on every messaging app you already use, answering from your own server with your own model keys. A single instance binds Discord, Telegram, Matrix, Slack, WhatsApp, Signal, email, and webhooks at once, so you can start a conversation on your phone and finish it at your desk without losing context. You choose the brain behind it: Anthropic, OpenAI, a local Ollama model, or any OpenAI-compatible endpoint, with fallback chains that keep the agent answering when one provider has a bad day. The agent acts through tools that run shell commands, drive a browser, call HTTP APIs, and talk to custom MCP servers you plug in. A web dashboard gives you chat, a memory browser, a configuration editor, cron job management, and a tool inspector from any browser. Long-term memory lives in SQLite on your disk with embedding-based recall, so past conversations stay searchable and private. Supervised autonomy is the default posture: medium-risk actions pause for your approval, high-risk actions are blocked outright, and operating system sandboxes plus cryptographic receipts keep every tool call bounded and auditable. Event-driven standard operating procedures react to MQTT messages, webhooks, schedules, and hardware events, and named agents let different personalities guard different channels. Registered as a system service, it stays online around the clock. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT or Apache-2.0 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.

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.

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.

While ordinary chatbots sit idle between prompts, Agenvoy runs around the clock on your own machine, turning one-sentence requests into finished research, files, and reports. Say what you need once and it builds the missing tool itself, tests that tool inside a sandbox, saves it, and reaches for it again the next time a similar job appears. Recurring work becomes a schedule in plain words; a morning briefing, a watched folder, or a weekly report then runs unattended, and a long task interrupted mid-run resumes from its checkpoint instead of starting over. Ask questions about your own files and it searches them like a private archive, transcribing audio and video into text it can quote back to you. Each task is routed to the model tier that fits it, a light model for lookups and a heavy one for hard reasoning, across subscription logins, API keys from eleven providers, or a local Ollama that never phones home. Commands run in a sandbox with the network off until you approve a call, sensitive paths ask before they open, and credentials wait in the system keychain instead of the chat history. You drive it from the terminal, the browser dashboard, or Telegram and Discord when you are away from the desk, and it lends its sandboxed tools to Claude Code and Codex over MCP. 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.

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.

Nakama gives your whole team a shared home for AI agents, where each agent has its own identity, memory, tools, and permissions and meets people where they already talk. The dashboard feels like a familiar chat app: pick an agent from the rail, start a conversation, and watch it use tools, recall memory, and reply inside Telegram, WhatsApp, Discord, or Slack when the work lives there. Every agent is configured as a small personality you can read and edit, with prompt files for its soul, style, instructions, and memory, plus tabs for its channels, tools, MCP servers, and skills. One server hosts many organizations with invites and roles, and agents stay isolated from each other so the support agent never wanders into the finance agent's toolbox. The control center manages workspace settings, model providers, plugins, and integrations, and a connector layer opens the door to more than a thousand external apps. Daily encrypted backups and an in-app update button keep operations boring, and the entire platform idles in about two hundred megabytes inside a single container. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

Sapphire is a self-hosted AI companion you can shape into a personal assistant, smart-home voice, or research partner that remembers conversations and acts through the tools you choose. Choose from twelve built-in personas or build your own, with each persona bundling its prompt, voice, tools, and model, and share personas, prompts, and toolsets as portable JSON files. Talk hands-free with wake word, speech-to-text, streaming text-to-speech, and barge-in, or type in chats that each keep their own prompt, tools, voice, and memory scope. Recall past details through semantic memory search, knowledge folders with file upload and folder watching, entity records for people and places, and hierarchical goals with a timestamped progress journal. Connect Discord, Telegram, email, Google Calendar, Home Assistant, Twilio phone calls, webcams, and image generation, then extend everything through one-click plugins, toolsets, and both an MCP server and an MCP client. Schedule heartbeats, morning greetings, alarms, background agents, daemons, and webhooks so the assistant checks in, follows goals overnight, and reports back when work finishes. Keep control with a privacy vault for encrypted chats, plugin signing and trust levels, in-app backup and restore, and a dashboard showing token metrics and system controls. 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.

Backed by $50M+ from Benchmark, Y Combinator, and NVIDIA with 800+ contributors and 39,000+ GitHub stars, MindsHub Cowork is the unified AI workspace where open-source models handle entire projects — research, reporting, internal tools, scheduled operations — and return finished, shareable deliverables. The platform runs two interchangeable open-source agent harnesses, Anton and Hermes, swappable from a dropdown without losing context. A built-in Model Router pre-wires 25+ models spanning Anthropic Claude, OpenAI GPT, Google Gemini, DeepSeek, Qwen, Kimi, Grok, and MindsHub Air with automatic failover — no per-provider API keys required. A secure credentials vault connects BigQuery, PostgreSQL, Salesforce, HubSpot, Zendesk, Gong, Gmail, Google Drive, Notion, Linear, Stripe, and Slack, keeping secrets scoped per connection so agents never see raw keys. Agent output becomes publishable artifacts — documents, dashboards, apps, and code — each deployable to a live shareable URL. Cross-session persistent memory, a reusable skill library, and a background scheduler supporting hourly, daily, and weekly cadences enable autonomous recurring workflows. The architecture separates a React/Vite frontend (shipping as both Electron desktop app and web SPA) from a FastAPI backend with a versioned REST API at /api/v1 covering conversations, projects, artifacts, schedules, and connectors. Self-host via Docker Compose with nginx on port 3000 and the API on port 26866, or deploy on-prem, in a VPC, or air-gapped. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

Recurring chores should get cheaper every time you run them, and Umpteenth is a self-hosted agent service built on that idea: describe a job once in plain language, and each run teaches it to need less help. A job starts on a schedule, a webhook call, the API, or the Run now button, and each run gets a fresh disposable container destroyed afterwards. The first run is an Explore run where the agent works out the steps; afterwards a reflection step reads the transcript and writes short learnings plus reusable toolkit scripts into a numbered playbook version. Later runs are Assisted, starting from those learnings, and after three successful assisted runs that take the same steps, the job graduates: reflection writes a main script, and scripted runs execute it alone, spending no model tokens unless a check asks for a judgment call. If a scripted check fails, the agent takes over in the same sandbox, finishes the job, and repairs the script. The job page charts cost per run dropping toward zero. Connect HTTP MCP servers such as GitHub or Slack; model keys and MCP credentials stay on the host and never enter the sandbox. Each job sets its own schedule, model, reach, and per run spending limit. Deploy with Docker Compose, or on Kubernetes with the Helm chart, where every sandbox is a pod. 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.

DopplerTask is the control layer where AI agents build your automations and you decide what goes live. You describe the outcome in plain language, and your agent assembles a task from a library of eighty-one ready-made steps spanning messaging, ticketing, sales, operations, documents, databases, queues, and AI models. The proposal lands in a visual editor that people and agents share, with new and changed steps marked and the old value of each field beside the new one. Nothing goes live until you approve it, and the previously approved version keeps running untouched in the meantime. Once a task is live it can start from a webhook, a schedule, a message queue, a manual click, or the agent itself, and every run is recorded with the output of each step, the person who started it, and the person who approved the version. Failed runs resume from the step that failed, with retries and continue-on-failure where you want them. Agents reference your credentials by name only; the values stay encrypted on your server, beyond the agent's reach, and separate tokens for people and agents plus single sign-on keep access tidy. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

Zapier's job, on your own server: Activepieces is an open-source workflow automation platform built to be exactly that replacement. Flows are built in a visual no-code editor with triggers, actions, loops, conditional branches, auto-retries, raw HTTP steps, and code steps that run JavaScript or TypeScript with full npm package support. Integrations are "pieces" - type-safe TypeScript npm packages with hot reloading for local development - and the catalog spans 600+ services, with the large majority contributed by the community. The platform is AI-first in two directions: native AI pieces call OpenAI, Anthropic, Google, and Azure models inside flows, and every piece automatically doubles as an MCP server, so assistants like Claude Desktop and Cursor can invoke your integrations and workflows through natural language. A built-in MCP server also exposes 30 tools for building flows, managing tables, and running tests agentically. Flows are fully versioned with draft and locked states. The core is MIT-licensed and runs on TypeScript with PostgreSQL and Redis.

Webhooks, cron schedules, and app events trigger chains of nodes that fetch, transform, and route data: n8n is a workflow automation platform built around a visual, node-based editor. It ships with 400+ built-in integrations covering databases like Postgres, SaaS tools like Slack and HubSpot, and every major AI provider. When a pre-built node does not exist, the HTTP Request node calls any REST API, and the Code node runs JavaScript or Python inline, so you are never blocked by a missing connector. Workflows execute as directed graphs with branching, loops, error handling, and sub-workflows, and every run is logged for inspection and replay during debugging. It also includes LangChain-based nodes for building AI agents with tool calling and memory. Self-hosting on RepoCloud gives you unlimited workflow executions with no per-task pricing, and all data stays on your instance. Runs on Node.js with SQLite by default; add Postgres and Redis queue mode when you need to scale workers horizontally.

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.

Always-on AI teammates that each get a real computer of their own, with a browser, files and a terminal, working from your hardware instead of a vendor cloud: that is OpenSuperBot. You hire a teammate from the sidebar with a name and a one-line job, and it works inside its own sealed computer with a browser, shell and persistent workspace. At a login wall the bot asks you to take over its live screen and sign in once inside its own browser profile, so passwords never pass through the gateway. Group threads let you ask the whole room at once: everyone answers in parallel, the chief of staff closes with a dispatch table, and @names pick which teammates respond. Nothing leaves the workspace without your say-so, because outward actions stop at a draft-and-hold approval chip. Standing approvals cover repeat sends to one destination for an hour or a day, and money and bookings always ask. Memory is a visible file you control: tell a bot a rule and it posts the exact change as a chip, and forget removes it the same way. Routines come from plain conversation, so a daily digest, a secret webhook trigger or a quiet status-page watch can be scheduled in chat. Each teammate runs a model you pick, with daily token budgets and live step cards for every action. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

AgenTerm lets your AI agent work inside a remote computer's terminal with the owner's permission, through a relay server you host yourself. Your agent connects to the server over MCP and creates an invitation, single-use and expiring in fifteen minutes by default, or reusable across several devices; you privately share the generated connection command with the person who needs help. That person runs a small client on macOS, Linux, or Windows, reads what access means, and authorizes it; the client then dials out to your server, so the target computer needs no SSH service and no open inbound port. The agent can then run one-off commands with a chosen working directory, environment overrides, and timeouts, receiving stdout, stderr, and exit status, or hold an interactive session open, reading output as it arrives and typing answers to prompts. The person at the keyboard watches every command and its output in the client and can disconnect at any moment, and the client reconnects by itself after a network drop. Use it to troubleshoot a colleague's machine without swapping logs, help family through a terminal problem, or drive a development box with no agent or model account of its own. The relay itself is a single Go binary guarded by a management key, deployed with Docker Compose or systemd, with in-memory sessions and a health endpoint. 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.