Markus is an AI workforce you run yourself: describe a goal in plain language and a team of specialist agents plans it, splits it into tasks, does the work, and reports back. A built-in Secretary agent hires agents from role templates, groups them into teams, and turns requirements into dependency-linked tasks. Work runs in parallel, each task in its own workspace, and a peer reviewer approves or sends back every delivery before it counts as done. Follow progress on a backlog table, a kanban board, or a dependency graph that shows which task unblocks which. Agents keep persistent memory, patrol their own task board around the clock, and can join team group chats or take direct messages. Connect Slack, Telegram, Discord, WhatsApp, or Feishu so people can reach agents where they already talk, and give agents browser and desktop automation through an optional Chrome extension. Pick any model provider, including Anthropic, OpenAI, Google, DeepSeek, OpenRouter, or a local Ollama server, and import skills from MCP servers or community hubs. A REST and WebSocket API, usage rankings, and an audit trail round out the control room. 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.

Start an AI task, close the tab, and come back to finished work waiting in an inbox. Pizza Bot keeps agents running when you navigate away or disconnect, sorting results into Unread for completed work and Action for approvals that need your decision. Conversations can be grouped into folders, pinned, searched, and forwarded from any message, without hiding matching items from the global queues. Schedules run a prompt on a cron expression with a time zone, and webhooks start a run from an external alert. A shared pool of Markdown memories carries your preferences into every conversation. Skills package step-by-step playbooks with scoped tools, and plugins bundle skills with MCP servers, so a request can be handed to a specialist subagent whose progress shows in an Activity panel. Connect Amazon Bedrock, Anthropic, Google Gemini, OpenAI, OpenRouter, Requesty, Opper, or Ollama, or point OpenAI at any compatible endpoint. Local folders are visible to the agent only after you grant them, read-only by default. Open it in the browser from one container behind a bearer token, or use the desktop app or terminal client against the same server. 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.

The invoices, reconciliations, and report downloads your team repeats every week are exactly the work a robot should be doing at 2 a.m. Astron RPA is an open-source robotic process automation platform: business users assemble workflows in a visual designer from more than three hundred pre-built components for clicking through desktop applications, driving browsers, reading and writing Excel and PDF files, querying databases, and calling APIs, then robots execute those workflows on schedule, on demand, through API calls, or through MCP services. The platform covers Windows desktop software and web pages alike, reaching office suites, browsers, and the finance and ERP systems that never grew an API, and Python scripting extends any step the components do not cover. A built-in excellence center and team marketplace let organizations publish shared automations, manage permissions, monitor executions, and reuse each other's robots across departments instead of rebuilding the same process ten times. AI components and a native agent platform connect language models to the workflows, so an agent can reason about a task and hand the clicking to a robot, and a workflow can call the agent back when judgment is needed. Self-hosters run the control plane themselves with Docker: database, identity service, and web console behind their own domain and certificates. 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.

Wire nodes together in a browser, deploy in one click, and real-time data flows from sources through transformations to outputs: Node-RED is the OpenJS Foundation's flow-based programming tool for event-driven applications. Born at IBM as a proof-of-concept for manipulating MQTT topic mappings, it has become the lingua franca of IoT and automation glue - home automation, industrial control, edge data collection - with a community library of over 5,000 contributed nodes and flows covering protocols, devices, and services. Where visual wiring runs out, JavaScript function nodes written in a rich in-editor code editor take over, and every flow serializes to importable, exportable JSON that shares cleanly and version-controls sensibly. Version 5.0 (2026) delivered the largest editor overhaul in the project's history: a rethought layout with Explorer and Information panels in a split sidebar, a native dark theme with theme variants, improved accessibility, and refreshed node appearance. The runtime is lightweight Node.js, exploiting the event-driven non-blocking model so the same flows run on a Raspberry Pi at the network edge or a cloud VM. Apache-2.0 licensed with 240+ contributors, it pairs naturally with dashboard nodes for live charts and controls.

Kaloscope manages your media library the way a flowchart thinks: search, download, scrape, rename, shelve, and play, each step a node you can see and rearrange. Drag HTTP requests, Python scripts, conditions, and loops onto the canvas to build the exact pipeline your sources need, then import community templates from GitHub when someone has already solved your problem. Global search aggregates multiple indexers at once, and finished finds flow straight into aria2, qBittorrent, Transmission, or OpenList for cloud downloading, with keyword rules and schedules automating the recurring hunts. Libraries for movies, series, and other media watch folders in real time, scrape rich metadata with custom naming rules, and read or write NFO files alongside the media. Press play in the same interface: FLV, HLS, and MP4 stream with on-demand transcoding, hardware acceleration, danmaku comments, and resume points that follow you between sessions. An AI assistant can draft workflows from plain language, inspect logs, and manage downloads, and external AI clients connect over MCP with token permissions you control. Per-library permissions, themes, and an installable PWA round out a server the whole household can use. 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.

Ask for a job in plain words and an agent with its own private computer does it: it reads files, runs commands, calls connected apps, and reports back in the chat. Every user gets a persistent sandbox workspace, so one person's files and commands never touch another's. Type a new message mid-run and the agent picks it up without stopping, or press Stop at any time. For bigger jobs the agent starts sub-agents that work side by side, each on a model of its choice, and the chat shows what each one is doing. Skills teach it repeatable methods in the open Agent Skills format; upload a zip, write one by hand, or let the agent write its own, and use them from a slash menu. The Connections page links Linear, Notion, Jira, Stripe, and other apps through one-click OAuth sign-in, or any MCP server by address. Scheduled tasks run on a repeating or one-time schedule, and each run becomes a readable chat. Small personal apps like a to-do cockpit or budget view appear in the sidebar, and charts, plans, and forms can render right inside answers. A files browser, an artifacts panel, a command menu, light and dark themes, and a phone layout round out the interface. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

MateClaw delivers a multi-agent AI platform where digital employees run as persistent team members with roles, goals, and accumulated skills rather than stateless chat completions. The Spring Boot backend on Spring AI Alibaba provides ReAct iterative reasoning and Plan-and-Execute decomposition on a StateGraph runtime, with parallel delegation between employees and dynamic context pruning for multi-step tasks. Five career templates ship ready (Product Researcher, Customer Support, Knowledge Curator, Data Analyst, Executive Assistant) while custom employees inherit configurable backstories, pixel-art avatars, and dedicated tool bindings. The MCP integration supports stdio, SSE, and Streamable HTTP transports with per-employee tool isolation preventing capability bleed between agents. ACP bridges bring Claude Code, Codex, and other coding agents in as first-class employees. Workflow orchestration composes multiple employees and system actions into publishable linear DSL processes with seven step modes: sequential, fan_out, collect, conditional, await_approval, dispatch_channel, and write_memory. The trigger system wires cron schedules, webhooks, channel messages, employee lifecycle events, content matches, and workflow completions to automated flows. The Admin Runtime Console provides real-time visibility into running employees with token usage tracking and one-click force-recycle. Spring Boot Actuator monitoring, full audit trail, and per-channel error isolation deliver production-grade reliability. 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.

For teams that answer customers by email, UVdesk is a free, self-hosted helpdesk that keeps every conversation in one shared queue. Customers have three ways in: a connected mailbox, the support portal, or a public ticket link that opens a conversation without a login. Gmail, Yahoo, Outlook, or any IMAP mailbox can feed the queue, with no limit on how many. Agents work in a threaded ticket view, where they reply, forward to a colleague, leave private notes, add collaborators, and pin important messages. Saved replies answer repeat questions, and prepared responses set a status, tag, priority, or assignment from the ticket footer. Administrators route work through groups and teams, and agent privileges decide which tickets each person may see. Workflows run events, conditions, and actions in the background, while spam settings reject senders by address, domain, or IP. A knowledge base of folders, categories, and articles, with revision history and related articles, lets customers find answers without writing in. Customers can rate the support they received, and the Kudos report lists those ratings by agent, group, team, type, priority, customer, or source. Portal branding covers a logo, brand colors, a tag line, and custom CSS and JavaScript. The community edition places no cap on agents, groups, teams, customers, or tickets. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. OSL-3.0 licensed.

Give your team a shared chat workspace where AI bots sit next to people, answer questions, and pick up recurring work. Organize conversations into pods with channels and threads, and keep a private personal pod for each member. Mention a bot with @ to hand it a task, mention several and each one replies, or let a bot ask another bot for help. Every bot gets its own name, avatar, instructions, and model, picked from OpenRouter, Anthropic, OpenAI, Google Gemini, or any OpenAI-compatible endpoint you add. Connections link a pod to GitHub, Linear, Stripe, Notion, Sentry, Jira, any MCP server, or any HTTP API, and bots act through them with approvals where you want a human check. Routines run a bot on a schedule, a webhook, or a GitHub event, then post the result to the pod channel. Computers give bots an isolated machine for heavier jobs, and web search lets them look things up and cite pages. A Usage page breaks down what bots cost by bot, model, and pod. Use it for a support desk, an engineering ops room, a morning briefing, or a shared research assistant. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

What Gmail did for email, Octobox does for GitHub notifications: an ephemeral, unmanageable stream becomes an inbox you can actually triage. GitHub marks notifications read the moment you glance at them and lets old ones vanish days later; heavy maintainers end up building elaborate Gmail filter systems just to cope. Octobox - a Ruby on Rails app over PostgreSQL - syncs your notifications into a persistent inbox with an explicit archived state: mark a thread done, and if the issue or PR sees new activity, it pops back automatically, so nothing silently falls through. Triage is keyboard-driven with Gmail-style shortcuts (j/k to navigate, e to archive, m to mute, s to star), and multi-select clears noisy repositories in bulk. Filtering is where it earns its keep: slice by repository, organization, type, action, state, reason, CI status, labels, author, assignee, or bot origin, combine prefix search filters, and pin favorite searches to the sidebar. The optional GitHub App enriches entries with live PR/CI status and labels so you can decide without clicking through. Auto-archive rules clear merged PRs and closed issues; muting and snoozing silence the rest. A REST API supports integrations. Self-hosting keeps your notification metadata - a map of everything you work on - on your own server.

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.

OpenCode puts a capable coding agent in a browser tab, so a project on your server can be worked on from any device. Start a session, describe the change, and watch the agent read files, edit code, and explain what it did in plain language. A review panel lists every changed file with unified or split diffs, a file tree, and a git changes view, so nothing lands without a look. Sessions open as tabs, run in parallel, and keep a searchable history per project. The model picker spans more than 200 providers plus free hosted models, and any OpenAI compatible endpoint can be added from a config file, which keeps local and self-hosted models in reach. Settings offer top tabs, side tabs, or an inbox layout, optional permission auto-accept, steer or queue behavior for follow-up prompts, timeline detail levels, themes, and fonts. Extensions cover MCP servers, plugins, and skills, and custom agents and commands capture the team's habits. One-time pairing links connect a new browser or app to the server in seconds. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

Cronstable gives scheduled jobs what cron never had: retries when they fail, alerts when retries run out, a saved history of every run, and a dashboard to watch it all. Bring your existing crontab or define jobs in YAML, down to business-day schedules, hashed fleet spreading, and per-job time zones, then let failures retry with backoff while alerts head to email, Slack-compatible webhooks, Sentry, or an encrypted push to your phone. Every run is remembered, so history, live logs, and incident timelines answer what happened last Tuesday instead of shrugging. When jobs grow dependencies, they become durable workflows: task graphs with data sharing, dynamic fan-out, sensors, shared resource pools, and approval gates a human taps before the next step runs, with failed tasks replayed selectively instead of starting over. One machine or a whole fleet looks the same from the web dashboard, the terminal, or iOS, and a schedule linter quietly warns you about the job that can never run and the one daylight saving will skip. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

Recognized by the CNCF Landscape in the AI Agent – Workflow Orchestration category alongside Dify and Temporal, Astron Agent is iFLYTEK's fully open-source platform for building, deploying, and managing enterprise multi-agent systems — backed by 8,900+ GitHub stars and the production infrastructure behind one of China's largest AI companies. Unlike pip-install frameworks such as LangGraph, CrewAI, or AutoGen, Astron Agent ships as a complete microservices platform spanning 10+ services across Java, Python, Go, and TypeScript: a ReactFlow-based visual workflow builder for low-code agent orchestration, native integration with the Model Context Protocol (MCP) for tool calling, a built-in model management layer supporting iFLYTEK Spark, OpenAI, Anthropic, and on-premises MaaS deployments, and a multi-tenant Go authentication service powered by Casdoor. The standout differentiator is native RPA integration via the companion astron-rpa project (7,200+ stars), providing 300+ pre-built automation capabilities spanning browser, Office document, and enterprise system interaction — enabling agents to execute physical UI actions rather than only API calls. Infrastructure includes PostgreSQL for multi-tenant data isolation, MySQL for application metadata, Kafka for event streaming, Redis for caching, and MinIO for object storage, all orchestrated through Docker Compose with explicit health checks and dependency chains or production Kubernetes Helm charts. 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.

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.

Describe the task in plain words, pick the sources and model it may use, and an agent plans the workflow before running it. That is the core loop: agents build editable visual workflows from a task description, execute them on demand or on a schedule, and keep everything traceable. Prefer building by hand and the canvas offers 17 preconfigured steps, branching, undo and redo, JSON import and export, plus eight starter templates. Feed it real work by importing PDF, DOCX, XLSX, CSV, JSON, and text files, or by connecting folders, HTTP endpoints, and approved local programs. Upload a screen recording and it identifies the actions with timestamps, turning a demonstrated process into an editable workflow you can refine. Model calls go to the endpoint you choose: Ollama, LM Studio, vLLM, or any OpenAI-compatible service, local or cloud with your own credentials. Every run can be inspected step by step, cancelled mid-flight, and exported as JSON, CSV, or Markdown reports. Observations from completed runs land in a knowledge and learnings store, where you review them and promote the useful ones into reusable skills for the next task. The Docker release bundles the application with FFmpeg and local Whisper support, and your documents stay on your own machine. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. Apache License 2.0 licensed.

PenguinHarness turns a one-sentence description of the agent you need into a working app, then lets other agents tune it round after round until its benchmark score climbs. Nine self-improvement algorithms ship as plugins, including OPRO, APE, ACE, and AWM, and every candidate becomes a snapshotted version with its score recorded in an Evaluation Center. Seventeen ready-made benchmarks cover data analysis, repository fixes, workflow automation, and terminal science tasks. Agents read and act on web pages through a built-in browser panel or your own Chrome, and each agent can grow a hot-reloaded workbench page like a contract review desk with uploads and downloadable reports. Add a machine over ssh and conversations in that workspace run there, inside the same window. A Cost Center breaks down spend per run, trajectories show every turn on an execution timeline, and replies can carry forms, charts, and live widgets. An Agent API streams runs to outside apps, and agents can be reached from Feishu, QQ, Telegram, or WeChat. 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.

Run a whole fleet of AI agents as managed services, each with its own model, memory, schedules, and sandboxed workspace, from one admin console. Create an agent, point it at OpenAI, Anthropic, OpenRouter, or any OpenAI-compatible endpoint, store its API keys encrypted, and it is ready to chat in the browser. People sign in with a device key and get a session list, streaming replies, and file attachments. The Agents table shows status, last activity, sessions, errors, and token spend for the past 24 hours, and the Stats page tracks users, sessions, events, and total tokens. Cron or one-shot schedules let an agent send a daily brief, and each run is logged. Owner, user, and guest roles control who may talk to an agent or change it, and policy and approval tabs gate risky tool calls. Skills and MCP servers are registered once and enabled for one agent or the whole fleet, and instructions can be pushed to every agent at once. Sessions, memories, and secrets sit in PostgreSQL, so state persists across gateway restarts. Use it for an internal agent platform, a support desk, or one agent per customer. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.