rinadelph/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.
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> 💬 **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**
Monitor every agent's status, assigned tasks, and recent activity. The system automatically manages task dependencies, prevents conflicts, and ensures work flows smoothly from planning to implementation.
Quick Start
Python Implementation (Recommended)
Node.js/TypeScript Implementation (Alternative)
MCP Integration Guide
What is MCP?
The **Model Context Protocol (MCP)** is an open standard that enables AI assistants to securely connect to external data sources and tools. Agent-MCP leverages MCP to provide seamless integration with various development tools and services.
Running Agent-MCP as an MCP Server
Agent-MCP can function as an MCP server, exposing its multi-agent capabilities to MCP-compatible clients like Claude Desktop, Cline, and other AI coding assistants.
Quick MCP Setup
MCP Server Configuration
Create an MCP configuration file (mcp_config.json):
Using Agent-MCP with Claude Desktop
1. **Add to Claude Desktop Config**:
Open ~/Library/Application Support/Claude/claude_desktop_config.json (macOS) or equivalent:
2. **Restart Claude Desktop** to load the MCP server
3. **Verify Connection**: Claude should show "🔌 agent-mcp" in the conversation
MCP Tools Available
Once connected, you can use these MCP tools directly in Claude:
**Agent Management**
- create_agent - Spawn specialized agents (backend, frontend, testing, etc.)
- list_agents - View all active agents and their status
- terminate_agent - Safely shut down agents
**Task Orchestration**
- assign_task - Delegate work to specific agents
- view_tasks - Monitor task progress and dependencies
- update_task_status - Track completion and blockers
**Knowledge Management**
- ask_project_rag - Query the persistent knowledge graph
- update_project_context - Add architectural decisions and patterns
- view_project_context - Access stored project information
**Communication**
- send_agent_message - Direct messaging between agents
- broadcast_message - Send updates to all agents
- request_assistance - Escalate complex issues