With over 600 GitHub stars and a featured Show HN launch, Mission Control is the agent-first command center that replaces the chaos of manually shepherding AI agents with structured delegation, approval workflows, and autonomous execution. The Next.js 15 web UI delivers an Eisenhower priority matrix with drag-and-drop quadrants, a Kanban board tracking tasks through Not Started, In Progress, and Done columns, and a goal hierarchy with milestone progress bars — powered by shadcn/ui, Radix UI, and @dnd-kit. Six built-in agent roles — Researcher, Developer, Marketer, Business Analyst, Tester, and You — receive tasks through a token-optimized API compressing context by 92 percent to approximately 50 tokens versus 5,400 unfiltered. The autonomous daemon polls task queues on cron schedules, spawns Claude Code sessions via the official CLI, enforces concurrency limits, and auto-retries with loop detection that escalates to human decisions after three failures. Field Ops extends execution to 64 external services across 16 categories with working X, Ethereum with MetaMask signing, and Reddit adapters, protected by AES-256-GCM encrypted vault with scrypt key derivation, per-service and global spend limits, a circuit breaker, and three autonomy levels. All data lives in local JSON files with Zod validation and async-mutex locking ensuring safe concurrent writes, backed by 193 automated Vitest tests. 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.

Where AI agents and people share one real-time workspace, an agent blocked on your decision never waits unnoticed until morning, and that workspace is AgentRQ, a human-in-the-loop task manager for agent fleets. In that workspace agents pull assigned tasks over MCP, report progress as they work, ask questions in the open, and pause visibly instead of going dark. Cards travel from Not Started to Ongoing to Blocked to Done on a list or Kanban board, and a Blocked card returns to work the second you answer from any device. Sensitive tool calls wait for an Allow click; flip YOLO on a task and they proceed automatically, still recorded call by call in a searchable trajectory. A timeline under every task totals how long the agent worked, waited, or stayed blocked. Scheduling spawns tasks on a cadence, completed tasks fire named events, and events hand new tasks to subscribed workspaces, chaining a release pipeline without glue code. Each project lives in an isolated workspace with its own agent, memory, skills, and Slack channel, and workspace memory carries yesterday's lessons into today's session. Voice-dictated tasks transcribe on device, 55 ACP-compatible agents connect through one gateway, and agents running on your own machines expose their terminals and resource use remotely. 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.

Cotal puts your AI agents in one shared room: Claude Code, Codex, and OpenCode discover each other, message channels, hand off work, and ask you to approve the result. Post to a channel and every subscriber hears it; message one peer and the durable inbox holds it until they are free; address a role like reviewer and one available reviewer claims the job. Presence shows who is actually there, and attention modes decide which channel traffic may interrupt an agent mid-task. A manager starts and stops agent processes in tmux or cmux, here or on remote hosts you authorize, without sitting between their messages. For work that waits and branches, Cotal Lang programs launch agents, pause at human checkpoints with deadlines, and resume from their recorded steps after an interruption. Services join the same space by publishing command contracts that authorized agents can discover and invoke; the bundled Linear adapter shows the pattern. Supervise from a terminal console with the live roster and activity feed, or from the read-only browser dashboard and its graph of agents and channels. Spaces stay separate, every message carries a checked identity, and per-agent grants decide who may delegate, spawn teammates, or call a service. 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.

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.

Alook gives the coding agent on your machine a seat in the team chat, with its own handle, inbox, and room memberships, so colleagues can ask it for work the same way they would message a person. You create servers, channels, and direct messages where people and agents are both first-class members, and an agent keeps one persistent identity across every room it joins. Claude Code, Codex, Cursor, OpenCode, Pi, Grok, and Antigravity connect through a small daemon, so the agent keeps running on your own hardware while the room stays reachable from anywhere. Because the agent holds memory across rooms, it can pick up a thread in one channel, report progress in another, and move tasks forward without you relaying messages by hand. Inviting a teammate takes a link; they join the room and talk with your agent directly instead of waiting for you to copy answers back and forth. The same room follows you from desktop to phone, so a question asked at your desk is still there, with the agent's reply, when you check it later. Self-hosting runs the web app, realtime WebSocket service, email worker, and wake-up queue on your own server with a local database, started with a single npx command. 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 outcome once, in plain language, and a small crew of AI agents divides the work between them and reports back in the same chat. You type the request in the team chat; Boo Zero, the team lead, splits it into jobs on a shared board and hands each card to the teammate best placed to do it. Teammates run on Claude Code, Codex, Hermes, OpenClaw, or Clawboo's built-in runtime, and one team can mix them freely, so the researcher, the writer, and the coder can each work on their strongest tool. You follow every card live on the board and in the chat, watch the team graph to see who is doing what, and add a reviewer agent when a second pair of eyes matters. Finished work returns to Boo Zero, which pulls the pieces together and answers you in the chat. Ready-made teams from the marketplace cover marketing squads, dev teams, and research crews, and you can bring an API key from Anthropic, OpenAI, OpenRouter and more, a free local model through Ollama, or your ChatGPT subscription through the Codex CLI. Spend is tracked per team with budget warnings before costs surprise you. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

AgentConnect brings Claude Code, Codex, Grok Build, DeepSeek, and any other ACP-compatible coding agent into the chat channels and repositories where your team already works, each with a role of its own. Mention an agent in Slack, Microsoft Teams, Google Chat, Lark, Discord, or Telegram and it replies in the thread, calls on a colleague agent when needed, and keeps its session visible to teammates who can step in. Work can also start from a GitHub, GitLab, Gitea, or Azure DevOps pull request, a Linear issue, a webhook, or a schedule. The web console organizes the fleet into Agents, Sessions, Schedules, Tools and Skills, Knowledge, and Daemons views. Every agent gets its own memory, skills, MCP servers, workspace, and sandbox policy, and reviewed Knowledge pages can be published for all agents to search. Decisions route new conversations to specialist agents and pick the runtime and model for each session. Review bots can run several reviewers with separate instructions on one pull request. Set who may see each agent or session, which repositories it can touch, and which agents it may call. 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.

PandaDOS is a self-hosted control plane that turns Claude Code and Codex into long-running coding agents you direct through an issue queue from any browser, instead of babysitting a terminal. You file an issue with the outcome and acceptance criteria, and PandaDOS clarifies missing requirements, plans the work, picks the agent, and drives implementation, verification, and delivery in stages. Three approval levels, cautious, balanced, and automatic, decide which actions proceed alone; safe reversible steps continue automatically while destructive, irreversible, production, or secret-related decisions always come back to you. The browser workspace shows the real agent conversation, a native terminal, project files, Git history and diffs, and an execution summary, so you can inspect or intervene at any moment from a phone or laptop. Agents run on local or SSH-connected executor machines inside tmux sessions, and work sharing one repository is serialized while independent projects proceed in parallel without conflicting edits. Modules keep one assigned agent and durable project knowledge, so context from finished issues carries into the next task instead of evaporating when a chat ends. Teams can sign in through Feishu, ask the project manager questions in chat, and receive subscription notifications and approval cards on their phones. 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.

Instead of babysitting three coding agents in three terminal windows, you describe the work once and let Mikka run the team: its Coordinator bot plans the job, dispatches runs to Claude Code, Codex, or Cursor on your connected machines, and only interrupts you when a decision is actually yours. Every piece of work lives in a thread with its own conversation, so dispatched runs appear as cards that report progress, ask questions, and flag blocks while you watch, reply, or stop them from the web, desktop, or phone. Unclear requests come back as choice cards before anything runs, and finished work moves through review and verification runs, back to a fix run when a check fails, then to acceptance where the pull request merges as you. Runs use leases and checkpoints, so a machine that drops mid-task hands the work to another connected computer with the same repository. You can create your own bots beside the Coordinator, each with its own chat, memory, and threads, and answers can arrive as charts, tables, stat cards, and task chips with sources cited. Daemons connect over SSH or from the desktop app, other agents drive Mikka through MCP, and Telegram or Slack messages reach the Coordinator too. 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.

One self-hosted workspace holds your team's chat, tasks, notes, and calendar, and Deft lets AI agents work in it beside your people. People get real-time chat with spaces, direct messages, threads, mentions, reactions, files, and presence. Tasks open as Board, Table, Timeline, or Calendar views, with dependencies, subtasks, recurrence, and bulk actions. Notes, decisions, and channel memory become durable knowledge, with graph views and links back to the source conversation. Native calendar events sit beside read-only ICS subscriptions. Agent employees can join channels and receive task assignments. Tag the built-in assistant Defty to draft a task, answer a workspace question, or take a governed action, then review the proposal in an approval card before anything changes. Personal connections let Codex, Claude, ChatGPT, and other streamable HTTP MCP clients act as the signed-in user within revocable scopes. Approval tiers, trust levels, token scopes, revocation, activity history, and action receipts record who or what acted and what changed. OpenAI, Anthropic, OpenRouter, OpenAI-compatible endpoints, and local Ollama-style models are supported providers. Chat, tasks, notes, and calendars keep working with no AI key. Modules add company-specific records, relationships, and views, with a bundled Contacts module as the first example. 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-only licensed.

Kandev provides a command center for orchestrating AI coding agents across parallel workstreams. The Go backend paired with a Next.js frontend delivers kanban boards with drag-and-drop columns, pipeline workflow definitions with per-step agent handoffs, and an IDE-like review workspace combining file editor, file tree, terminal, browser preview, and unified git diffs. Multi-provider support connects Claude Code, GitHub Copilot, Codex, Qoder, Grok, and custom agents through configurable profiles with per-agent prompts, runtimes, and review gates. Tasks execute in isolated git worktrees with multi-repository support, letting agents work on separate branches simultaneously while changes surface in a consolidated review interface. Native integrations with GitHub, GitLab, Jira, Linear, Sentry, and Slack pull external issues into the kanban and link tasks to pull requests. Kandev exposes streamable HTTP and SSE MCP endpoints, enabling external clients — Cursor, Claude Desktop, Augment — to create tasks and read workspace context programmatically. Workflow definitions export as portable YAML for sharing across installations. Agentic workflows chain multi-step pipelines mixing different models per step — Opus for architecture, Sonnet for implementation, with human review gates between stages. 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.

Orbit puts your team's tasks, documents, and conversations in one workspace on your own server, so planning work no longer means checking three separate apps. Task projects carry your own workflow: switch between list, board, and timeline layouts, drag work between statuses, break large efforts into sub-issues, and link related tasks with an activity feed recording every change. Saved views keep preferred filters one click away, and personal pages like My tasks, This week, and Overdue show what needs attention today. Documents live in a page tree with teamspaces and favorites; the rich editor supports tables, code blocks, and checklists, several people can write at once with visible cursors, version history keeps earlier drafts recoverable, and a Notion importer brings existing pages across. Chat sits beside the work rather than in a separate silo: channels, direct messages, threads, files, reactions, and search, with links to tasks and pages unfolding into previews inside the conversation. GitHub sync turns labeled issues and pull requests into tasks and completes them when pull requests merge. AI clients connect through a built-in MCP server with OAuth, so an assistant can read your projects with the full context of your workspace while the data never leaves your server. Administrators manage workspaces, members, roles, API tokens, audit logs, and scheduled backups to S3 from the same interface. 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.

With nearly 5,000 GitHub stars and a Hacker News launch that garnered 147 points, Colanode delivers the first genuinely local-first alternative to both Slack and Notion in a single self-hosted workspace — writing every operation to a client-side SQLite database before syncing to your server, so teams work at full speed offline, on planes, or through intermittent connections without ever losing a draft. The real-time chat system provides channels and direct messages with instant delivery via WebSocket, while the rich text editor offers Notion-style block-based pages for documents, wikis, meeting notes, and knowledge bases with headings, code blocks, embeds, and nested hierarchies. Customizable databases organize structured data with custom fields and three dynamic views — table for spreadsheet-style browsing, kanban for visual workflow boards, and calendar for time-based planning. Conflict-free Replicated Data Types powered by Yjs handle concurrent editing across pages and database records: multiple users modify the same document simultaneously and the system merges changes automatically without manual conflict resolution. File management supports upload, sharing, and organization within workspaces using pluggable storage backends including local filesystem, S3-compatible services, Google Cloud Storage, and Azure Blob Storage with TUS resumable uploads for large files. The server runs Fastify with Zod validation on Node.js 20+, persists to PostgreSQL with pgvector extension, uses Redis for event broadcasting, and deploys via a single Docker image. 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 most-starred open-source project management platform on GitHub with over 55,000 stars, Plane delivers what Jira, Linear, Monday, and ClickUp charge thousands per year for — issue tracking, sprint planning, documentation, and AI-powered workflows in one unified workspace that you own and control entirely. Work items feature a rich text editor with file uploads, sub-properties, custom states, priorities, labels, assignees, and cross-referencing, organized across five customizable layout views (list, board, table, spreadsheet, Gantt) with Command-K navigation for instant access to anything. Time-boxed Cycles provide sprint planning with automatic burn-down charts, velocity tracking, and scope change detection, while Modules break complex projects into manageable deliverables with progress aggregation. Built-in Pages combine AI-powered documentation with rich formatting, image embedding, and one-click conversion of notes into actionable work items. The AI layer reads across every project, cycle, document, and thread in the workspace — agents take real assignments, triage incoming requests, assign owners, track blockers, and ship status updates automatically. Native integrations connect GitHub, GitLab, Slack, Sentry, Figma, and 50+ tools with bidirectional issue sync and PR tracking, while import pipelines migrate entire workspaces from Jira, Linear, Asana, ClickUp, or Monday in minutes. The REST API with OAuth 2.0, HMAC-signed webhooks, typed SDKs in Node.js and Python, and a native MCP server enable custom automations. 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.

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.

Describe the change in chat, and LoopForge opens a Docker sandbox, checks out your repositories, hands the work to specialist agent roles, and opens the pull request. That is the conversational path: a Main Bot coordinates planning, implementation, review, and testing roles, each with its own prompt, executor, model, rules, skills, and tools, and you can queue or steer messages mid-reply, then pause, resume, or take over a run at any point. When a way of working proves itself, you freeze it as an SOP: a visual canvas of agent steps, deterministic script steps, human gates, and sub-workflows that every requirement then follows in the same order with the same checks. Four built-in SOPs cover backend delivery, frontend delivery, product proposals, and bug fixes, and each one can be copied, edited, and versioned per project. A Needs review inbox collects every gate waiting on you, with per-node status, tool traces, logs, and artifact snapshots as the evidence behind each approval. Recurring AI tasks run on schedules with the same workspace and workflow access, and insights reports track engineering metrics and token costs per run and per conversation. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT 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.

Agent Zero equips large language models with a persistent virtual Linux desktop, letting autonomous AI agents write code, research the web, and execute multistep tasks without supervision. Operating within an isolated container, the system opens an interactive XFCE graphical desktop in your browser canvas where the agent interacts with GUI applications like Blender and terminal sessions directly. Its embedded browser features interactive annotation tools, letting you click web elements to inspect stylesheet hierarchies, extract component markup, or submit automated testing instructions. You can cowork on spreadsheets, presentations, and Markdown specifications in real time alongside the agent, preserving document revisions through snapshot time travel. A multi-tier memory architecture backed by FAISS vector indexing and SearXNG web discovery retains problem-solving context across projects, while hierarchical delegation spins up specialized subordinate agents to parallelize complex engineering audits. The platform connects seamlessly to commercial LLMs via OpenAI, Anthropic, or OpenRouter, runs private local models through Ollama, and integrates custom toolkits via the Model Context Protocol and community Plugin Hub. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.