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.

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.

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.

Your coding agents work in separate terminals and cannot ask each other anything; Imbo gives Claude Code, Codex, opencode, Cursor CLI, and six other agent tools one shared messaging network, so a session can send a question to another session and get an answer while both keep working. Messages land inside the receiving session mid-task, and a reply wakes an idle session so it can act on the answer. You add people by account ID, and their agents can message yours; group chats let several sessions from several people coordinate on one brief, with every reply reaching every member. Sessions can send files that land in the receiving machine's ~/.imbo/files folder, and an agent asks you first before sending your data out, deleting files, spending money, or touching production. From the web app or the iPhone app you can message your own sessions from anywhere, and a closed Claude Code session reopens in the background to pick the message up. The server is a single binary with a bundled PostgreSQL, HTTPS through Let's Encrypt, email code sign-in, and optional domain restrictions on who may register. 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.

Mention an AI agent in a channel the way you would page a teammate, and it picks up the surrounding conversation, claims the task, does the work in its own persistent workspace, and reports back in the thread. OpenTag is a self-hosted, Slack-style workspace where people and coding agents from Claude Code, Codex, GitHub Copilot, and other runtimes work as one team across channels, threads, DMs, and a shared task board. Each agent keeps its own memory file, runtime session, permissions, and activity history, can be started, stopped, put to sleep, woken, or resumed, and can delegate pieces of a job to other agents or schedule reminders that wake it later. Teams watch live progress through per-message activity that expands to show thinking, status, and tool calls, while full-text search keeps every decision findable where it was made. The control plane runs from Docker Compose on your server, connected machines run the daemon that hosts the agent CLIs, and attachments, databases, and workspaces stay on infrastructure you control. Multi-workspace accounts, scoped permissions for agents and members, and per-channel task numbering keep larger teams organized without surrendering their context to someone else's cloud. 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.

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.

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.

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.

SuperPlane is an open-source engineering automation platform that turns routine backlog tickets into verified, review-ready pull requests while orchestrating complex multi-system workflows across your developer tools. Engineers use the visual infinite canvas to assemble event-driven pipelines with trigger nodes, conditional routing, loops, and human-in-the-loop approval gates. You can delegate pull request code reviews, automated QA testing, documentation generation, and release management to coding agents operating within strictly defined policy boundaries. Custom operational consoles let teams build live monitoring dashboards displaying key delivery metrics, active incident states, and execution histories from connected tools. Integrations connect natively with GitHub, GitLab, Datadog, PagerDuty, Slack, AWS, and leading AI models through webhook events and bi-directional actions. Every automation run maintains durable state persistence across process restarts, ensuring failed steps resume with full input payloads and debugging context intact. Developers can define reusable work orders, configure canvas memory for long-term state retention, and execute fleet commands over SSH or containerized runners. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. Apache 2.0 licensed.

Your GitHub pull requests get reviewed by your own models, with inline findings posted in the merge flow: Codra is a self-hosted AI code review engine, so your diffs and credentials stay inside infrastructure you control. Connect a repository once and every opened, synchronized, ready-for-review, or reopened pull request starts a queued review job automatically; mention Codra for an on-demand pass instead. Findings arrive as inline GitHub comments, a summary review, and check run updates that fit the normal merge flow. Each repository gets its own review personality: triggers, skipped paths, draft handling, mention reviews, labels, custom rules, and a review budget are all tuned from the dashboard, and model routing follows global defaults, per-repository chains, fallbacks, and size-based overrides for larger pull requests. Providers from OpenAI, OpenRouter, Anthropic, Google, NVIDIA, and Cloudflare are managed behind GitHub OAuth sign-in. The operator dashboard tracks totals for reviews, input and output tokens, and comments posted, then drills into job history, webhook deliveries, failed queue runs, and model usage, so a stalled review is debuggable instead of invisible. Deploy the whole loop (GitHub App, web server, queue, database, and dashboard) on Cloudflare Workers, on Node.js 24, or with Docker on your own server. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. AGPL-3.0 licensed.

Kodus AI automates pull request code review with inline AI comments across GitHub, GitLab, Bitbucket, and Azure DevOps, supporting any LLM provider at cost with zero token markup. The multi-service TypeScript architecture deploys via Docker Compose, running an API server, background worker, webhooks service, and React dashboard backed by PostgreSQL with pgvector, MongoDB, and RabbitMQ. Integration covers both cloud platforms and their enterprise flavors (GitHub Enterprise Server, GitLab Self-Managed, Bitbucket Data Center) using standard OAuth flows and webhook signing to keep the review loop entirely inside your network. The platform is model-agnostic with Bring Your Own Key support for Claude, GPT, Gemini, Llama, and any OpenAI-compatible endpoint including locally-hosted models. Custom review rules combine your team's coding standards with requirements pulled from Jira, Linear, and Notion, automatically checking every PR against documented specifications. The CLI enables local reviews against working trees, staged diffs, branches, or specific commits, integrating into CI/CD pipelines as pre-merge gates. Source code is never stored and never used for model training, with all data encrypted in transit and at rest. 1,270+ stars and 129+ releases since March 2025. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. AGPL-3.0 licensed.

Inside your Git platform, AI-Git-Bot works as a self-hosted teammate that quietly handles the engineering chores everyone agrees matter and nobody has time for. Open a pull request and it reviews the diff with inline findings, re-reviews after a force-push, and answers questions when you mention it in the discussion, keeping the conversation context across updates. Assign it an issue and it can rewrite that issue with structure and acceptance criteria, route it to the right assignee with a stated reason, or implement it and open a pull request for you. It generates unit tests for new code, builds Playwright end-to-end suites and runs them against a preview environment, then posts the results back to the pull request. Documentation and locale files stop drifting, because README sync and translation coverage workflows update them as the code changes. Every run is observable through built-in metrics and signed outgoing webhooks, and you choose the brain behind it, from cloud models to a local model on your own hardware, so source code never has to leave your network. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. MIT licensed.

Originated as Alibaba Group's official internal AI code review assistant serving tens of thousands of developers and identifying millions of code defects over two years before open-sourcing in May 2026 — now at 21,000+ GitHub stars — Open Code Review is the production-hardened platform that proves enterprise-grade code review can be fully open-source under Apache 2.0. The hybrid architecture separates deterministic engineering pipelines (file selection, diff parsing, rule matching for NPE, thread-safety, XSS, and SQL injection across 10+ languages) from LLM-powered agent reasoning with tool-use capabilities including FileRead, CodeSearch, and cross-file context inspection, consuming approximately one-ninth the tokens of general-purpose coding agents while delivering line-level precise comments with severity and confidence scoring. The bundled web dashboard (port 4173) provides review management, findings triage, result browsing, and direct GitHub posting without external dependencies, while the session viewer (port 5483) renders full LLM request/response traces for debugging and auditing. Integration spans GitHub Actions, GitLab CI, GitFlic CI, and Gerrit with delegation mode enabling Claude Code, Cursor, and other AI agents to leverage OCR's engineering logic alongside their own LLM reasoning. Supports OpenAI, Anthropic, Google Gemini, DeepSeek via built-in providers plus Ollama and vLLM for air-gapped deployments. 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.

One endpoint for every MCP server you run: MCPHub gathers local and remote Model Context Protocol servers behind stable URLs, so AI clients connect once and see what you allow. Claude Code, Cursor, and Cherry Studio can use four routes: everything at /mcp, a named group at /mcp/{group}, one server at /mcp/{server}, or semantic tool search at /mcp/$smart. Smart routing runs vector search on PostgreSQL with pgvector and an OpenAI-compatible key, so the model gets a shorter tool list. Servers attach over stdio, SSE, or streamable HTTP, OpenAPI services can be wrapped as MCP tools, and changes apply without downtime. In the other direction, MCP tools can be exported as an OpenAPI 3.0.3 spec for OpenWebUI and other OpenAPI clients. Bearer keys, OAuth 2.0 (client and server modes), and GitHub or Google sign-in in database mode control access, with per-user visibility for servers and groups. Encrypted per-user credentials let one shared server use each person's own key. Logs show tool-call activity, request status, and latency, health checks track each connection, and the dashboard controls which tools, prompts, and resources each server exposes. Large text tool results can be compressed, interactive MCP Apps are proxied through MCPHub routes, and a built-in market lets you browse a server catalog. Typical uses include a team-wide gateway, per-project groups, and direct single-server routes for debugging. 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.

Teams that cannot send messages through someone else's cloud run Mattermost - the open-core, self-hosted alternative to Slack. It provides public and private channels, threaded discussions, unlimited search history, file sharing with previews, one-to-one audio calls, and screen sharing, with desktop clients for Windows, macOS, and Linux plus iOS and Android apps. Messages support full Markdown, which suits engineering conversations with code blocks and logs. Playbooks turn repeatable processes such as incident response and release management into checklist-driven workflows with automated triggers and retrospectives. Integration is a core strength: prebuilt connectors for GitHub, GitLab, Jira, ServiceNow, and PagerDuty, plus webhooks, slash commands, bots, a REST API, and a plugin marketplace with 700+ entries - together making it a working surface for ChatOps rather than just a chat room. Playbooks add keyword and event triggers, task assignment, status broadcasting, and post-incident retrospectives, so operational knowledge is not trapped in individuals' heads. The server is a single Go binary backed by PostgreSQL, with React clients, released monthly under MIT license and deployable fully air-gapped - which is why governments and defense organizations run it inside closed networks, and why the same control applies to any team with confidentiality requirements. The compiled Team Edition is free for unlimited users with no message history cutoff, so costs stay flat as the team grows.