Agent8 MCP Server
Powers AI functionality for generating or processing code examples, such as embeddings for vector search.
Provides vector database storage and retrieval for code examples used in Agent8 game development.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Agent8 MCP Serversearch for code examples about sprite movement"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
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-sdkprompt template.
Tools
Code Examples Search: Retrieves relevant Agent8 game development code examples from a vector database using the
search_code_examplestool.
Installation
# Install dependencies
pnpm install
# Build
pnpm buildUsing Docker
You can run this application using Docker in several ways:
Option 1: Pull from GitHub Container Registry (Recommended)
# 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:latestOption 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-serverDocker Environment Configuration
There are three ways to configure environment variables when running with Docker:
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-serverUsing individual
-eflags: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-serverUsing Docker Compose (for development/production setup):
The project includes a pre-configured
docker-compose.ymlfile 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 upTo run in detached mode:
docker compose up -d
Required Environment Variables:
SUPABASE_URL: Supabase URL for database connectionSUPABASE_SERVICE_ROLE_KEY: Supabase service role key for authenticationOPENAI_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 --versionSupported 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.
Create a
.envfile in the project root (see.env.examplefor reference):
# Copy the example file
cp .env.example .env
# Edit the .env file with your settings
nano .envRun the server (it will automatically load the
.envfile):
pnpm startOr specify a custom path to the
.envfile:
pnpm start --env-file=/path/to/custom/.envConfiguration Priority
The server uses the following priority order when determining configuration values:
Command line arguments (highest priority)
Environment variables (from
.envfile or system environment)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
Variable | Description | Default |
MCP_TRANSPORT | Transport type (stdio or sse) | stdio |
PORT | Port to use for SSE transport | 3000 |
LOG_LEVEL | Log level (debug, info, warn, error) | info |
LOG_DESTINATION | Log destination (stdout, stderr, file, none) | stderr (for stdio transport), stdout (for sse transport) |
LOG_FILE | Path to log file (when LOG_DESTINATION is file) | (none) |
DEBUG | Enable debug mode (true/false) | false |
SUPABASE_URL | Supabase URL for database connection | (required) |
SUPABASE_SERVICE_ROLE_KEY | Supabase service role key for authentication | (required) |
OPENAI_API_KEY | OpenAI API key for AI functionality | (required) |
Using Stdio Transport
# Build and run
pnpm build
pnpm start --transport=stdioUsing SSE Transport
# Build and run (default port: 3000)
pnpm build
pnpm start --transport=sse --port=3000Debug Mode
# Run in debug mode
pnpm start --debugAvailable Prompts
systemprompt-agent8-sdk
Client Integration
Using with Claude Desktop
Add the following to Claude Desktop configuration file (
claude_desktop_config.json):
{
"mcpServers": {
"Agent8": {
"command": "npx",
"args": ["--yes", "agent8-mcp-server"]
}
}
}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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