🚀 Multi Agent MCP: The Multi-Orchestrator AI Coding Agent

Multi Agent MCP is a high-performance, model-agnostic Model Context Protocol (MCP) Server designed to transform your IDE into an autonomous multi-agent coding assistant.

Integrating directly with Claude Desktop, Cursor AI, and Windsurf, Multi Agent MCP orchestrates complex codebase refactoring using LangGraph and LiteLLM. Instead of relying on a single zero-shot prompt, this framework deploys a specialized swarm of AI agents to strategically plan, confidently verify, and surgically write code within a secure Git Sandbox.

🌟 Why Multi Agent MCP? (Features)

When searching for an MCP Agent or AI Coding Assistant, you usually find single-prompt algorithms that risk hallucinating over large codebases. Multi Agent MCP solves this by combining deterministic graphs with fluid LLM swarms:

• 🧠 Multi-Orchestrator Architecture: Uses a graph state machine (LangGraph) to manage complex developer workflows and prevent infinite agent loops.

• 🛡️ Git Sandbox Security: Automatically isolates autonomous AI work on separate feature branches (optional) to protect your main codebase from destructive edits.

• ⚡ Model Agnostic & Local Ready: Purely powered by LiteLLM. Native support for Claude, OpenAI, Local LLMs, and hyper-optimized for Groq (Llama 3.3 70B).

• 🔍 AST-Aware File Context: Reads the Abstract Syntax Tree (classes/functions) before fetching raw code strings to minimize context token overwhelm.

• 🎯 Direct Editing Mode: Toggle isolate: false in the MCP Tool schema to have the AI swarm apply code modifications directly to your current working branch.

Related MCP server: MCP Refactoring

🛠️ Installation & Setup

1. Prerequisites

• Python 3.10+

• Git initialized in your target project directory.

2. Install Dependencies

pip install mcp langgraph litellm python-dotenv pydantic

3. Configure Environment

Create a .env file in the root of your workspace:

# Fast/Free Groq example
GROQ_API_KEY=gsk_your_key_here
SWARM_MODEL="groq/llama-3.3-70b-versatile"

4. Run the Agent Server

python src/server.py

🔌 Connecting to IDEs (MCP Integration)

Connect this AI Agent tool directly into your daily development environment:

Cursor / Windsurf

1. Open Settings -> MCP.

2. Add a new server:

   • Name: Multi Agent-MCP

   • Type: command

   • Command: python c:/absolute/path/to/src/server.py

Claude Desktop

Add the following configuration to your claude_desktop_config.json:

{
  "mcpServers": {
    "Multi Agent-mcp": {
      "command": "python",
      "args": ["c:/absolute/path/to/src/server.py"]
    }
  }
}

🌍 Open Source & Distribution

Multi Agent MCP is built natively for the open-source Smithery.ai MCP registry and GitHub discovery algorithms. Ensure you configure your .gitignore correctly before pushing your own forks!

See the OPENSOURCE.md guide for more details on integrating this repo.

📜 License

MIT License.

Keywords for discovery: Model Context Protocol, MCP Server, AI Agent, Multi-Agent System, Coding Assistant, LangGraph orchestrated agent, Claude tool integration, Cursor AI MCP, Windsurf, coding swarm, autonomous developer.