docs/MCP_IMPLEMENTATION_SUMMARY.md

MCP Implementation Summary

Overview

This document summarizes the implementation of Model Context Protocol (MCP) support for the RTS Commander game.

Features Implemented

1. MCP Server (mcp_server.py)

• Created a FastMCP server that runs on port 8001
• Integrated with the existing game infrastructure
• Exposes game state and actions through the Model Context Protocol

2. Tools

Implemented the following tools for AI agents to interact with the game:

1. get_game_state() - Returns the current game state as JSON
2. get_ai_analysis(language) - Returns AI tactical analysis in the specified language
3. move_units(unit_ids, target_x, target_y) - Moves units to a target position
4. attack_unit(attacker_ids, target_id) - Commands units to attack an enemy unit
5. build_building(building_type, position_x, position_y, player_id) - Builds a structure
6. **send_game_command(command_type, kwargs) - Sends a generic command to the game

3. Resources

Implemented the following resources for AI agents to access game information:

1. game_documentation - Provides the game's README documentation
2. game_rules - Provides the game's architecture and rules documentation

4. Integration

• Integrated with the existing handle_command method in the ConnectionManager
• Uses the existing AI analysis system for tactical advice
• Accesses game state through the global manager instance

Testing

Unit Tests

• Created test_mcp_server.py for basic server functionality testing
• Created test_mcp_integration.py for integration testing

Test Coverage

• Server creation and configuration
• Tool registration
• Resource registration

Documentation

New Files

• docs/MCP_INTEGRATION.md - Complete integration guide
• docs/MCP_IMPLEMENTATION_SUMMARY.md - This document
• examples/mcp_client_example.py - Example client usage
• examples/README.md - Examples directory documentation

Updated Files

• README.md - Added MCP integration section
• docs/README.md - Added MCP integration to documentation index
• docs/PROJECT_FILES_INDEX.txt - Added MCP files to project index
• tests/README.md - Added MCP tests to test documentation
• requirements.txt - Added MCP package dependency

Usage

Starting the Servers

To start both the main game server and the MCP server:

python start_with_mcp.py

Or start them separately:

# Terminal 1: Start main game server
python start.py

# Terminal 2: Start MCP server
python mcp_server.py

Connecting an AI Client

AI clients can connect to the MCP server at localhost:8001.

For example, with Claude:

claude --mcp-server localhost:8001

Implementation Details

Architecture

The MCP server is implemented as a separate FastAPI application that runs alongside the main game server. It communicates with the game through the existing ConnectionManager instance.

Security

The MCP server runs on a separate port (8001) from the main game server (7860) to isolate AI access from player connections.

Extensibility

The implementation is designed to be easily extensible:

• New tools can be added by implementing new methods in the _register_tools method
• New resources can be added by implementing new methods in the _register_resources method

Future Improvements

1. Authentication - Add authentication for MCP clients
2. Rate Limiting - Implement rate limiting for commands
3. Input Validation - Add more comprehensive input validation
4. Advanced Tools - Add more sophisticated tools for complex game interactions
5. Real-time Updates - Implement real-time game state updates through MCP

Conclusion

The MCP integration provides a robust foundation for AI agents to interact with the RTS Commander game. It exposes all necessary game information and actions through a standardized protocol, making it easy for AI agents to understand and control the game.