MCP Server for Agent8

by planetarium
Verified

hybrid server

The server is able to function both locally and remotely, depending on the configuration or use case.

Integrations

  • Supports configuration via .env files for managing environment variables

  • Provides containerized deployment options through Docker, including GitHub Container Registry integration

  • Offers container image distribution through GitHub Container Registry

MCP Server for Agent8

A server implementing the Model Context Protocol (MCP) to support Agent8 SDK development. Developed with TypeScript and pnpm, supporting stdio and SSE transports.

Features

This Agent8 MCP Server implements the following MCP specification capabilities:

Prompts

  • System Prompt for Agent8 SDK: Provides optimized guidelines for Agent8 SDK development through the system-prompt-for-agent8-sdk prompt template.

Tools

  • Code Examples Search: Retrieves relevant Agent8 game development code examples from a vector database using the search_code_examples tool.
  • Game Resource Search: Searches for game development assets (sprites, animations, sounds, etc.) using semantic similarity matching via the search_game_resources tool.

Installation

# Install dependencies pnpm install # Build pnpm build

Using Docker

You can run this application using Docker in several ways:

# Pull the latest image docker pull ghcr.io/planetarium/mcp-agent8:latest # Run the container docker run -p 3333:3333 --env-file .env ghcr.io/planetarium/mcp-agent8:latest

Option 2: Build Locally

# Build the Docker image docker build -t agent8-mcp-server . # Run the container with environment variables docker run -p 3333:3333 --env-file .env agent8-mcp-server

Docker Environment Configuration

There are three ways to configure environment variables when running with Docker:

  1. Using --env-file (Recommended):
    # Create and configure your .env file first cp .env.example .env nano .env # Run with .env file docker run -p 3000:3000 --env-file .env agent8-mcp-server
  2. Using individual -e flags:
    docker run -p 3000:3000 \ -e SUPABASE_URL=your_supabase_url \ -e SUPABASE_SERVICE_ROLE_KEY=your_service_role_key \ -e OPENAI_API_KEY=your_openai_api_key \ -e MCP_TRANSPORT=sse \ -e PORT=3000 \ -e LOG_LEVEL=info \ agent8-mcp-server
  3. Using Docker Compose (for development/production setup):The project includes a pre-configured docker-compose.yml file with:
    • Automatic port mapping from .env configuration
    • Environment variables loading
    • Volume mounting for data persistence
    • Container auto-restart policy
    • Health check configuration

    To run the server:

    docker compose up

    To run in detached mode:

    docker compose up -d

Required Environment Variables:

  • SUPABASE_URL: Supabase URL for database connection
  • SUPABASE_SERVICE_ROLE_KEY: Supabase service role key for authentication
  • OPENAI_API_KEY: OpenAI API key for AI functionality

The Dockerfile uses a multi-stage build process to create a minimal production image:

  • Uses Node.js 20 Alpine as the base image for smaller size
  • Separates build and runtime dependencies
  • Only includes necessary files in the final image
  • Exposes port 3000 by default

Usage

Command Line Options

# View help pnpm start --help # View version information pnpm start --version

Supported options:

  • --debug: Enable debug mode
  • --transport <type>: Transport type (stdio or sse), default: stdio
  • --port <number>: Port to use for SSE transport, default: 3000
  • --log-destination <dest>: Log destination (stdout, stderr, file, none)
  • --log-file <path>: Path to log file (when log-destination is file)
  • --log-level <level>: Log level (debug, info, warn, error), default: info
  • --env-file <path>: Path to .env file

Using Environment Variables

The server supports configuration via environment variables, which can be set directly or via a .env file.

  1. Create a .env file in the project root (see .env.example for reference):
# Copy the example file cp .env.example .env # Edit the .env file with your settings nano .env
  1. Run the server (it will automatically load the .env file):
pnpm start
  1. Or specify a custom path to the .env file:
pnpm start --env-file=/path/to/custom/.env

Configuration Priority

The server uses the following priority order when determining configuration values:

  1. Command line arguments (highest priority)
  2. Environment variables (from .env file or system environment)
  3. Default values (lowest priority)

This allows you to set baseline configuration in your .env file while overriding specific settings via command line arguments when needed.

Supported Environment Variables

VariableDescriptionDefault
MCP_TRANSPORTTransport type (stdio or sse)stdio
PORTPort to use for SSE transport3000
LOG_LEVELLog level (debug, info, warn, error)info
LOG_DESTINATIONLog destination (stdout, stderr, file, none)stderr (for stdio transport), stdout (for sse transport)
LOG_FILEPath to log file (when LOG_DESTINATION is file)(none)
DEBUGEnable debug mode (true/false)false
SUPABASE_URLSupabase URL for database connection(required)
SUPABASE_SERVICE_ROLE_KEYSupabase service role key for authentication(required)
OPENAI_API_KEYOpenAI API key for AI functionality(required)
ENABLE_ALL_TOOLSEnable or disable all tools globallytrue
ENABLE_VECTOR_SEARCH_TOOLSEnable or disable all vector search toolstrue
ENABLE_CINEMATIC_TOOLSEnable or disable all cinematic toolstrue
ENABLE_CODE_EXAMPLE_SEARCH_TOOLEnable or disable code example search tooltrue
ENABLE_GAME_RESOURCE_SEARCH_TOOLEnable or disable game resource search tooltrue

Tool Activation Priority: The tool activation settings follow this priority order:

  1. Individual tool settings (e.g., ENABLE_CODE_EXAMPLE_SEARCH_TOOL)
  2. Tool group settings (e.g., ENABLE_VECTOR_SEARCH_TOOLS)
  3. Global tool setting (ENABLE_ALL_TOOLS)

For example, if you set ENABLE_ALL_TOOLS=false but ENABLE_VECTOR_SEARCH_TOOLS=true, only vector search tools will be enabled while other tools remain disabled. Similarly, individual tool settings override their respective group settings.

Examples:

# Enable only vector search tools ENABLE_ALL_TOOLS=false ENABLE_VECTOR_SEARCH_TOOLS=true # Disable a specific tool while keeping others enabled ENABLE_ALL_TOOLS=true ENABLE_CODE_EXAMPLE_SEARCH_TOOL=false

Using Stdio Transport

# Build and run pnpm build pnpm start --transport=stdio

Using SSE Transport

# Build and run (default port: 3000) pnpm build pnpm start --transport=sse --port=3000

Debug Mode

# Run in debug mode pnpm start --debug

Available Prompts

  • systemprompt-agent8-sdk

Client Integration

Using with Claude Desktop

  1. Add the following to Claude Desktop configuration file (claude_desktop_config.json):
{ "mcpServers": { "Agent8": { "command": "npx", "args": ["--yes", "agent8-mcp-server"] } } }
  1. Restart Claude Desktop

Adding New Prompts

Add new prompts to the registerSamplePrompts method in the src/prompts/provider.ts file.

License

MIT

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A server implementing the Model Context Protocol (MCP) to support Agent8 SDK development by providing system prompts and code example search capabilities through stdio and SSE transports.

  1. Features
    1. Prompts
    2. Tools
  2. Installation
    1. Using Docker
  3. Usage
    1. Command Line Options
    2. Using Environment Variables
    3. Using Stdio Transport
    4. Using SSE Transport
    5. Debug Mode
  4. Available Prompts
    1. Client Integration
      1. Using with Claude Desktop
      2. Adding New Prompts
    2. License
      ID: 72qko8mjvv