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.

Paca is a self-hosted project management platform and Scrumban workspace where autonomous artificial intelligence agents collaborate with human software engineers as first-class Scrum teammates instead of external chat assistants. Engineering teams manage sprints, backlogs, and task lifecycles through a shared real-time board powered by Socket.IO where both humans and agents pick up assignments and post progress updates. A native Model Context Protocol server connects external coding assistants such as Claude Desktop and Claude Code directly into projects, tasks, and sprint data without custom scraping scripts. Distributed agents execute in isolated runtime sandboxes powered by the OpenHands software development kit, co-authoring behavior-driven development Gherkin scenarios with product owners and maintaining living system design documents. Visual event-driven automation builders compose multi-branch trigger, condition, and action pipelines that evaluate task dependency gates and cron schedules. A sandboxed WebAssembly plugin runtime allows developers to write custom backend logic and custom board views using Go or Rust. 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.

Edict is a multi-agent orchestrator that runs every AI request through a court-style chain: a crown prince agent triages it, a planning department drafts the work, a review department can veto the plan, and specialist ministries execute what survives. Casual chat gets a direct reply, while real commands become kanban tickets whose titles are scrubbed of file paths and metadata. A vetoed plan returns for rework; an approved one is dispatched in parallel to ministries for finance, documentation, engineering, compliance, infrastructure, and HR. Commands arrive through Feishu, Telegram, or Signal channels configured in OpenClaw. The dashboard shows cards by state with heartbeat badges and stop, cancel, and resume controls, plus a department monitor and a memorial archive that turns finished work into five-phase timelines you can copy as Markdown. Nine edict templates add parameter forms and cost estimates, an officials panel ranks agents by merit score while tracking token spend, and per-agent model switching restarts the gateway in about five seconds. Agent thinking, tool calls, and results stream live. A permission matrix limits who may message whom, illegal state jumps are rejected, and every transition lands in an audit log. Worked examples cover competitive analysis, code review, and weekly reports. Dashboard login protects the console, and a systemd unit keeps it running across reboots. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

A drag-and-drop task board that works fine on its own and can also hand cards to AI coding agents, Veritas Kanban shows what each agent is doing, what it changed, and what is waiting for your approval. Start with no agents at all. Cards move through To Do, In Progress, Blocked, and Done, and each one carries subtasks, dependencies, time tracking, comments, and an activity log. When you are ready, connect Codex, Claude Code, Copilot CLI, Hermes, or OpenClaw, give every agent an Intern, Specialist, or Lead permission level, and follow each agent's status and model on a live dashboard. Let a task run in its own Git worktree, read the diff, leave inline comments, approve or request changes, and open a GitHub pull request from the task panel. Squad Chat gives agents one shared channel that posts spawned, completed, and failed events. Workflows chain steps with parallel branches, loops, and human approval gates. Policy rules allow, deny, or hold agent actions for review. Assistants reach the board through an MCP server, a command-line client, or a REST API. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT 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.

Your coding agents finish a session, close the laptop, and forget everything; Pad is where the project remembers. It holds the tasks, plans, bugs, ideas, and decisions in one workspace that you drive from a browser while your agents drive it from the terminal, so the next session, human or machine, picks up exactly where the last one stopped. You plan on boards, lists, and tables with drag-and-drop status columns, rich item pages, comment threads, and a dashboard that answers what needs attention and what to do next. Your agents read the queue, claim items, leave checkpoints, link their pull requests, and mark work fixed with the fixing PR attached. Conventions teach them the house rules once, like running tests before calling a task done, and playbooks hand them repeatable multi-step workflows they can invoke by name. Every change is versioned with its author, a person or a named agent, and new items appear in the browser the moment an agent creates them in the terminal. The same workspace is reachable three ways: the web interface, the pad CLI, and a bundled MCP server with a natural-language skill that plugs into Claude Code, Cursor, Codex, Windsurf, OpenCode, Copilot, Amazon Q, and Junie. 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.

OverClick is the task board where your AI agents clock in: you write the assignments, they claim the work, and you stamp what actually got done. A card here is a contract, not a ticket: what should happen, why it matters, and a plain-language test script that says how to confirm it, all written before anyone starts. You tell your agent to grab the next task, and it claims the card over MCP, declares the CLI and model it really runs on, receives a self-contained briefing with the mission context and branch convention, and the card slides into progress. When it finishes, the handoff lands with a summary, evidence, branch and pull request links, and measured telemetry, the tokens per model and minutes the run actually took, read from the session transcript rather than guessed. Every card keeps three roles straight, who asked, who executed, and who reviews, and only a human can mark it validated; reopening with a comment puts your note in front of the agent's next claim. Big decisions can start as RFC cards whose approval spawns the execution cards, and insights roll up what each project, mission, and model consumed. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

Autonomous AI coding agents work side-by-side with software engineers inside Its a Plan, a keyboard-driven project tracking and sprint planning workspace designed for rapid software delivery. Product teams organize development cycles through customizable Kanban boards, prioritized backlogs, nested sub-issues, and interactive roadmap timelines designed for rapid keyboard navigation. Engineers can assign work directly to AI agents or mention them inside discussion threads to trigger automated code fixes, documentation updates, and test suite generation. Integrated runners connect to popular coding models via standard protocol interfaces, executing assigned tasks in isolated environments before reporting pull requests and results back to the issue thread. Administrators manage team permissions through role-based access controls, authenticate users with passwordless passkeys or identity providers, and broadcast instant notifications via Telegram and transactional email. The platform dispatches configurable webhooks across development tools, enabling seamless bi-directional status synchronization with external version control platforms and continuous integration pipelines. Custom labels, milestone estimates, and progress metrics provide engineering managers with immediate visibility into sprint velocity and delivery bottlenecks. 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.

With over 77,000 GitHub stars accumulated in under five months since its March 2026 launch, Paperclip has become the default control plane for teams running multiple AI agents in production. Rather than juggling dozens of terminal tabs with Claude Code sessions, Codex instances, and Gemini CLI workers, Paperclip organizes all agents into a company structure with org charts, reporting lines, role-based permissions, and per-agent monthly budgets that trigger hard-stops when exceeded. The platform supports any runtime through its adapter system — Process adapters manage local CLI agents like Claude Code, Codex, Cursor, Pi, and OpenCode as child processes, while HTTP adapters trigger remote agents via webhooks to OpenClaw, serverless platforms, or custom endpoints. Heartbeat-based execution wakes agents on configurable schedules, injecting goal context, budget state, and workspace paths directly into the invocation payload. The Work and Task System provides atomic checkout with execution locks, first-class blocker dependencies, and structured work products to eliminate duplicate effort. Governance features include approval workflows, decision tracking, emergency stops, and full audit trails tracing every mutation to an actor. Deployment runs as a single Node.js process with embedded PostgreSQL locally or scales to external Postgres for production, installable in one command via npx paperclipai onboard. 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 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.

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.

Trinity runs your AI agents the way a company runs employees, with departments, roles, reporting lines, and receipts for everything they do. Each agent holds a seat on record tied to an objective and a declared metric, so whether it is working is a number with a date on it rather than an impression. Agents work on three runtimes, Claude Code, OpenAI Codex, and Gemini CLI, chosen per chat without changing the agent's state, history, or permissions. A schedule fires, the agent works inside its own container, and anything irreversible waits in a human approver's Inbox as a card naming the agent, the skill, and the input until someone approves, discusses, or rejects it. Every agent is a git repository you own: it commits its own work, its tool calls land in an append-only audit log, and every run appears in an execution ledger with its trigger, cost, and outcome, searchable across the fleet. The same agents answer in the browser Workspace, in Slack, Telegram, and WhatsApp, over a public chat link, through MCP, and from the CLI. Guardrails bind agents by what they hold rather than what they are told, with hooks they cannot switch off, cost limits, loop budgets, and a kill switch for outbound 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.

Platypus gives a whole team always-on AI agents that reason, call tools, and keep working on your own servers while everyone is offline. Build an agent once by choosing a provider and model, writing its instructions, and capping its tool-calling loop, then reuse that preset across chats and scheduled runs. Agents load reusable Skills on demand and delegate specialist work to sub-agents that appear to the parent as tools. Connect local and remote data through Model Context Protocol servers, or expose an agent to outside agents and chat platforms through A2A endpoints with a token per client. Triggers run agents on a cron schedule, as one-off jobs, or when workspace events such as a card moving on a board occur, and every run records its result. Kanban boards give agents work they can move and update themselves, while notifications and HMAC-signed webhooks push board and workspace events into your own systems with filtering and retries. Facts and preferences are extracted from conversations in the background and injected into future chats, so returning users are remembered. Sandbox backends give agents shell and filesystem access inside an isolated per-workspace environment instead of the host. Organizations and workspaces keep each team's agents and data separate, and blueprints package shared agents, skills, MCP servers, and providers so a new workspace starts pre-equipped. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

Winner of the 2015 Most Valued Agile Tool award and cited as a top project management platform by Opensource.com with over 2,100 GitHub stars on the Docker deployment repository alone, Taiga has served an estimated 20 million users worldwide with over 2 million Docker pulls since its creation in 2014 by Kaleidos. The platform delivers a complete agile project management experience through Scrum boards with backlog prioritization, sprint planning, story point estimation configurable per role, burndown charts at both project and sprint levels, and velocity tracking with a project doom-line indicator. Kanban boards offer customizable workflow columns with swimlanes, WIP limits, zoom controls, and the ability to switch between Scrum and Kanban at any point without losing data. The issue tracker supports custom types, priorities, and severities with the ability to promote issues directly to user stories. Team collaboration features include threaded comments, file attachments, email notifications, mentions, a built-in wiki for project documentation, and a team performance dashboard with the Iocane health metric for tracking team sustainability. The platform integrates with GitHub, GitLab, and Bitbucket for version control linking, provides importers for migrating from Trello and Jira, and exposes a REST API for custom integrations. Available in over 20 languages with custom fields, tags, roles, and permissions. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MPL-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.

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.