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Glama

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

Related MCP server: Claude Team MCP

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.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.

No tool schema history has been recorded yet.

Maintenance

ActivityStale
ResponsivenessSyncing

Resources

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MCP directory API

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curl -X GET 'https://glama.ai/api/mcp/v1/servers/echodeveloperio/agent-mcp'

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