Agent-MCP 是一个用于创建多智能体系统的框架，通过模型上下文协议（MCP）实现协调高效 AI 协作。
概览
🚀 ： 该框架面向需要复杂多代理编排能力的资深AI开发者。Agent-MCP需要熟悉AI编码工作流程、MCP协议和分布式系统概念。我们正积极改进文档和易用性。如果你是AI辅助开发新手，建议从更简单的工具开始，需要高级多代理能力时再回来使用。💬： 在Discord上与我们联系，获取帮助、分享经验，并与其他构建多代理系统的开发者协作。 多智能体协作协议，用于协调AI软件开发。 Think——一个活生生的知识图谱，多个AI代理通过共享上下文、智能任务管理和实时可视化协作。观看你的代码库演变，专业代理并行工作，永不丢失上下文，也不会互相干涉。
概述（AI 翻译）
🚀 高级工具通知：该框架面向需要复杂多代理编排能力的资深AI开发者。Agent-MCP需要熟悉AI编码工作流程、MCP协议和分布式系统概念。我们正积极改进文档和易用性。如果您是AI辅助开发新手，建议从更简单的工具开始，需要高级多代理能力时再回归。
💬 加入社区：在Discord上与我们联系，获取帮助、分享经验，并与其他构建多代理系统的开发者协作。
多智能体协作协议，用于协调AI软件开发。
想想Obsidian为你的AI代理——一个活生生的知识图谱，多个AI代理通过共享上下文、智能任务管理和实时可视化协作。看着你的代码库演变，专业代理并行工作，永不丢失上下文，也不会互相干涉。
为什么要多名经纪人？
除了哲学问题外，传统的AI编码助手还面临实际局限：
- 大型代码库中的上下文窗口溢出
本页由 AI 翻译，技术细节请以原文为准。
README
以下为原文 README 节选，完整内容请查看原文。
Agent-MCP
🚀 Advanced Tool Notice: This framework is designed for experienced AI developers who need sophisticated multi-agent orchestration capabilities. Agent-MCP requires familiarity with AI coding workflows, MCP protocols, and distributed systems concepts. We’re actively working to improve documentation and ease of use. If you’re new to AI-assisted development, consider starting with simpler tools and returning when you need advanced multi-agent capabilities.
💬 Join the Community: Connect with us on Discord to get help, share experiences, and collaborate with other developers building multi-agent systems.
Multi-Agent Collaboration Protocol for coordinated AI software development.
Think Obsidian for your AI agents - a living knowledge graph where multiple AI agents collaborate through shared context, intelligent task management, and real-time visualization. Watch your codebase evolve as specialized agents work in parallel, never losing context or stepping on each other’s work.
Why Multiple Agents?
Beyond the philosophical issues, traditional AI coding assistants hit practical limitations:
- Context windows overflow on large codebases
- Knowledge gets lost between conversations
- Single-threaded execution creates bottlenecks
- No specialization - one agent tries to do everything
- Constant rework from lost context and confusion
The Multi-Agent Solution
Agent-MCP transforms AI development from a single assistant to a coordinated team:
Real-time visualization shows your AI team at work - purple nodes represent context entries, blue nodes are agents, and connections show active collaborations. It’s like having a mission control center for your development team.
Core Capabilities
Parallel Execution
Multiple specialized agents work simultaneously on different parts of your codebase. Backend agents handle APIs while frontend agents build UI components, all coordinated through shared memory.
Persistent Knowledge Graph
Your project’s entire context lives in a searchable, persistent memory bank. Agents query this shared knowledge to understand requirements, architectural decisions, and implementation details. Nothing gets lost between sessions.
Intelligent Task Management
安装
This server does not publish a one-line install command.
Open the repository installation guide 新手？先看 mcpskill.org 教程 →配置
{
"mcpServers": {
"agent-mcp": {
"command": "uv",
"args": ["run", "-m", "agent_mcp.cli", "--port", "8080"],
"env": {
"OPENAI_API_KEY": "your-openai-api-key"
}
}
}
}