agentrq MCP Server
agentrq/agentrq
[](https://agentrank-ai.com/tool/agentrq--agentrq/?utm_source=badge&utm_medium=readme&utm_campaign=agentrank_badge) AgentRQ: Human-in-loop realtime conversational task manager for AI Agents. Self-hosted! Control your own agents from wherever you want Mobile, Web, Desktop. Designed to work well with your own Claude subscriptions and any harness with ACP support.
claude mcp add agentrank -- npx -y agentrank-mcp-server Overview
agentrq/agentrq is a Go tool licensed under AGPL-3.0. AgentRQ: Human-in-loop realtime conversational task manager for AI Agents. Self-hosted! Control your own agents from wherever you want Mobile, Web, Desktop. Designed to work well with your own Claude subscriptions and any harness with ACP support. Topics: agentic-ai, agentic-workflow, agents, task, task-manager, task-scheduler, acp-client, mcp, mcp-server, acp-gateway, dsh-plugin, claude-code, hermes-agent, opencode, claude-plugin, gemini-cli-extension, ai-memory, mcp-memory, mcp-skills.
Ranked #56 out of 24849 indexed tools.
In the top 1% of all indexed tools.
Has 1,139 GitHub stars.
Has 17 contributors.
Actively maintained with commits in the last week.
Ecosystem
Score Breakdown
1,139 stars → well-known project
Last commit today → actively maintained
19/20 issues closed → responsive maintainer
17 contributors → active community
No dependents → no downstream usage
Weights: Freshness 20% · Issue Health 20% · Dependents 22% · Stars 10% · Contributors 8% · How we score →
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[](https://agentrank-ai.com/tool/agentrq--agentrq/?utm_source=badge&utm_medium=readme&utm_campaign=agentrank_badge) <a href="https://agentrank-ai.com/tool/agentrq--agentrq/?utm_source=badge&utm_medium=readme&utm_campaign=agentrank_badge"><img src="https://agentrank-ai.com/api/v1/badge/agentrq--agentrq" alt="AgentRank"></a> Matched Queries
From the README
# AgentRQ ── Agent-Human Collaboration Platform
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<a href="README.zh-CN.md">简体中文</a>
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<a href="https://discord.gg/xFSMaEA2b2">
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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.
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<td wid Read full README on GitHub → Get the weekly AgentRank digest
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