AgentRQ ── Agent-Human Collaboration Platform

简体中文

AgentRQ is a modern, high-performance platform designed for seamless collaboration between human operators and AI agents. It leverages the Model Context Protocol (MCP) to allow AI models (like Claude) to interact directly with your workspace's task management system.

🚀 Overview

Think of AgentRQ as a shared workspace where humans and AI agents work together seamlessly. You can break down complex goals into manageable tasks, and delegate work directly to your AI agents.

Because agents "see" the workspace state via MCP, they can autonomously pull their assigned tasks, update statuses, request permissions for sensitive actions, and communicate with you—all synchronized instantly across the platform in real-time.

✨ Features

Real captures from the running app — no mockups.

Visual Task Board

Every task Claude creates appears instantly on your board. See what it's working on, what it needs, and what it just finished — all from a clean, fast dashboard you can open on any device, as a list or a Kanban.

Task Scheduling

Give any task a launch date, or a recurring cadence — every 15 minutes, hourly, daily, weekly, custom days. A background poller ticks every minute and spawns the task the instant it's due, no server or agent needing to stay awake and wait.

Events

Events are named signals — qa_passed, deploy_finished, blog_published — that any task can fire when it completes. Wire one to a workspace and that workspace gets a new task automatically, no polling and no glue code.

Workflows

A Workflow is Events and workspaces arranged on a graph. Drag a workspace onto an event to subscribe it; drag an event onto a workspace to emit it on completion. No decision-tree DSL, no YAML — just the shape of your release process, visible.

Tool Call History

The task detail view's History tab lays out a lane-grouped timeline of every tool call and message in a run — Input, Agent, and Tools. Search it, click into any entry, and see exactly what ran, what it returned, and whether it was allowed or denied.

Auto-Title Generation

Write your task description, click the sparkle, and a small language model — downloaded once and cached by your browser — reads it and writes the title. No API call, no server, no data leaving your machine.

Speech-to-Text

Click the mic on any task description or reply and dictate it instead. Transcription runs on an in-browser Whisper model — your voice is processed on-device and never uploaded anywhere.

Message Send Delay

Give a workspace a countdown — 3s, 5s, 10s, 15s, 30s or 60s — and every chat message waits that long in the thread before it reaches the agent. Send Now delivers it early, Cancel pulls it back unsent and puts the exact text and attachments back in your composer. Off by default, per workspace.

Search & Keyboard Shortcuts

⌘K (Ctrl+K off macOS) opens a task finder that matches any word in a title or description, straight from the copy your device already saved — so it answers offline, and tells you how far it looked. Everything else is a bare letter: N for a new task, W and M to jump to a workspace or a machine, C and T to flip between a task's chat and its trajectory, ? for the list. Nothing to configure, and nothing to memorise.

Machines

Install agentrqd on a computer you own, enrol it once with a single-use code typed on the machine itself, and it becomes somewhere agents can run — in your repositories, with your toolchain. Pick a workspace and what to run, and it starts in that workspace's folder on that machine. Each machine's page shows what it has left: CPU, memory, uptime, load and free space per filesystem.

Live Terminals

Open a running session from any browser and you are at the prompt. Keystrokes go straight through as the bytes your keys produced — Esc and Ctrl-C included — resizing reflows the program on the far end, and the session keeps running whether or not anybody is watching. Drop the network and the screen is still there when you come back.

Skills

Give a workspace's agents the playbooks your team already follows. A skill is a SKILL.md plus the files it points to, in the same format Claude Code uses. Paste a public GitHub link, such as obra/superpowers, and every skill in it is imported. Write your own, or let an agent save one. Skills belong to your account: turn each one on in the workspaces that need it, and they all read the same copy, so an edit reaches every one of them. Every agent that connects to the workspace is told to search its skills at the start of a task and load the ones that match, over MCP, whatever harness it runs in. How skills work →

Workspace Forks

Fork a workspace to have a second agent take some of its tasks in parallel. Right-click it in the sidebar to fork it, or choose Spin up on a task, which forks the workspace, moves the task in and launches an agent in one step. The fork has its own queue and agent. It shares the parent's memory, skills and settings, and runs in its own git worktree or copy of the parent's folder. When its tasks are done, merge it back: its agent is stopped and every task returns to the parent with its thread. How forks work →

See the full list at agentrq.com/features.

🏛 Architecture

AgentRQ follows a decoupled service-oriented architecture:

Backend (Go / Fiber)

• API Server: Fiber-based REST API for workspace and task management.
• MCP Server: Integrated mcp-go SSE server that exposes tools and resources to AI models.
• CoreMCP (Supervisor): A global MCP server that allows agents to manage all workspaces, tasks, and statistics across the entire platform.
• Data Layer: GORM