MCP Servers

agent-mcp

Enables collaborative software development through a team of specialized AI agents (Architect, Developer, Reviewer, Tester) communicating via the Model Context Protocol, with tools for file management, task tracking, and code review.

Category

README

MCP Agent Team

A multi-agent system for collaborative development using the MCP (Model Context Protocol).

Architecture

agent-mcp/
├── mcp-server/     # MCP protocol server
├── agents/         # Specialized AI agents
├── memory/         # Shared state storage
└── config/         # Configuration

Agents

Agent	Role	Capabilities
Architect	Architecture planning	Project analysis, design patterns, tech stack decisions
Developer	Code implementation	Task execution, code generation, permission workflow
Reviewer	Code quality	Security checks, bug detection, code standards
Tester	Quality assurance	Test planning, failure analysis, coverage estimation

MCP Tools

list_files - List files in directories
get_file_content - Read file contents
create_task - Create tasks in shared queue
update_task - Update task status
send_message - Agent-to-agent communication
get_messages - Retrieve messages
read_project_context - Analyze project structure
review_code - Static code analysis

Quick Start

# Install dependencies
pip install -r requirements.txt

# Run MCP server
python -m mcp_server.server

# Or with Docker
docker build -t agent-mcp .
docker run -p 8080:8080 agent-mcp

Integration

OpenCode MCP Config

{
  "mcpServers": {
    "agent-team": {
      "command": "python",
      "args": ["-m", "mcp_server.server"],
      "cwd": "/path/to/agent-mcp"
    }
  }
}

Kilo AI Connection

The MCP server exposes a stdio interface compatible with Kilo AI's MCP client for agent communication.

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