defcon-mcp-server

defcon-mcp-server

Enables AI tools to play the game DEFCON by providing tools to communicate with the game, analyze game state, and issue commands such as placing structures, moving fleets, and launching nukes.

Category
Visit Server

README

DEFCON MCP Server

This is a Model Context Protocol (MCP) server for Introversion Software's 2007 game DEFCON, which allows your favourite AI tool to play GLOBAL THERMONUCLEAR WAR.

(work in progress; not all commands are available yet!)

Setting up

  1. Install DEFCON. Make sure to start it once to load your CD key.
  2. Download the DEFCON AI API and extract v1.57 to your DEFCON installation folder. You may want to rename the AI API .exe to DEFCON_ai.exe.
  3. Download LUABOT and extract it to <defcon installation folder>/AI; rename the folder so that you have <defcon installation folder>/AI/luabot/luabot.dll.
  4. Git clone this repository into the luabot folder.
  5. The MCP server writes to an input text file, which the Lua bot reads. The lua bot then writes to an output text file which is read by the MCP server. You will have to set the file paths yourself; they're hardcoded to write to R:\input.txt and R:\output.txt by default, but you can supply inputfile and/or outputfile CLI arguments to Defcon to override tis. A RAMDisk is recommended if you can set one up.
  6. Install dependencies with npm ci in this repository folder.
  7. Start the game via .\Defcon_ai.exe host nowan nolan nowlan luabot="AI\luabot\main.lua" numplayers=2 territory=0 debug inputfile="D://input.txt" outputfile="D://output.txt". Select AI/luabot/luabot.dll as the "external bot", and then add an internal AI player as well. The game should start automatically; if it doesn't just ready up to start!
  8. Configure your MCP-enabled LLM interface to start the MCP server via node mcp-server.mjs (for stdio transport) or node mcp-server.mjs --http (for HTTP transport). You can pass --inputfile="D://input.txt" and --outputfile="D://output.txt" or similar to set the location of input/output text files.
  9. Watch the carnage unfold!

Architecture

The DEFCON MCP Server uses a multi-layered architecture to enable AI-powered gameplay:

  1. Game Layer: DEFCON game running with the AI API extension
  2. Lua Bridge: A Lua bot (main.lua) that interfaces with the game through the DEFCON AI API
  3. File I/O Layer: Communication between the Lua bot and MCP server via text files
    • input.txt: Commands from MCP server to the game
    • output.txt: Game state information from the game to the MCP server
  4. MCP Server Layer: Node.js server (mcp-server.mjs) implementing the Model Context Protocol
    • Provides standardized tools, resources, and prompts for LLM interaction
    • Supports both stdio and HTTP transport methods
  5. LLM Integration Layer: Your AI tool connects to the MCP server to analyze game state and issue commands

Data Flow

  1. The Lua bot reads the game state and writes it to output.txt
  2. The MCP server reads output.txt to get the current game state
  3. The LLM analyzes the game state and decides on actions
  4. The MCP server writes commands to input.txt
  5. The Lua bot reads input.txt and executes commands in the game

Command Correlation

The system uses correlation IDs to track command execution:

  • Each command sent to the game includes a unique ID
  • Command results are tagged with the same ID
  • This allows the MCP server to verify if commands were executed successfully

Available MCP Tools

The MCP server provides the following tools:

  • debug-log: Send a debug message to the game log
  • send-chat: Send a chat message to opponents
  • place-structure: Place a structure (RadarStation, Silo, or AirBase) at specified coordinates
  • place-fleet: Place a fleet of ships at specified coordinates
  • move-fleet: Move a fleet to specified coordinates
  • whiteboard-draw: Draw a line on the whiteboard
  • whiteboard-clear: Clear all lines from the whiteboard
  • launch-nuke: Launch a nuclear missile from a silo to target coordinates
  • set-silo-defensive: Set a silo to defensive mode
  • get-command-results: Retrieve results of previously executed commands
  • get-game-state: Get the latest game state information
  • generate-ai-response: Generate an AI response based on the current game state

Available MCP Resources

The MCP server provides the following resources:

  • defcon://game-state: Get the current game state
  • defcon://level: Get the current DEFCON level

Available MCP Prompts

The MCP server provides the following prompts:

  • analyze-game-state: Analyze the current game state and suggest optimal moves
  • suggest-structure-placement: Suggest optimal locations for structure placement
  • suggest-nuke-targets: Suggest optimal targets for nuclear strikes

Recommended Servers

playwright-mcp

playwright-mcp

A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.

Official
Featured
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.

Official
Featured
Local
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.

Official
Featured
Local
TypeScript
VeyraX MCP

VeyraX MCP

Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.

Official
Featured
Local
graphlit-mcp-server

graphlit-mcp-server

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.

Official
Featured
TypeScript
Kagi MCP Server

Kagi MCP Server

An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

Official
Featured
Python
E2B

E2B

Using MCP to run code via e2b.

Official
Featured
Neon Database

Neon Database

MCP server for interacting with Neon Management API and databases

Official
Featured
Qdrant Server

Qdrant Server

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Official
Featured
Exa Search

Exa Search

A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.

Official
Featured