返回 MCP 目录
public公开dns本地运行

MCP Agent8 开发助手

一个实现模型上下文协议(MCP)的服务器,通过标准输入输出(stdio)和服务器发送事件(SSE)传输方式,为Agent8 SDK开发提供系统提示和代码示例搜索功能支持。

article

README

MCP Server for Agent8

A server implementing the Model Context Protocol (MCP) to support Agent8 SDK development. Developed with TypeScript and pnpm, supporting stdio, SSE, and streamable-http 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.
  • Asset Generation: Comprehensive toolset for game asset creation:
    • Images: Generate 2D game assets using the image_asset_generate tool
    • Cinematics: Create cinematic sequences with cinematic_asset_generate tool
    • Audio: Generate music tracks and sound effects with music_generate and sfx_generate tools
    • Skyboxes: Create 360° environmental backgrounds with skybox_generate tool
    • Support Tools: Status checking, result retrieval, and wait utilities for asynchronous generation

Installation

# Install dependencies
pnpm install

# Build
pnpm build

Using 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: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_TRANSPORTS=sse,streamable-http \
      -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
  • --transports <types>: Transport methods (comma-separated: stdio,sse,streamable-http), default: stdio
  • --port <number>: Port to use for HTTP-based transports (sse, streamable-http), 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

| Variable | Description | Default | | --------------------------------- | ---------------------------------------------------------------------------------- | ---------------------------------------------------------- | | MCP_TRANSPORTS | Transport methods (comma-separated: stdio,sse,streamable-http) | stdio | | PORT | Port to use for HTTP-based transports (sse, streamable-http) | 3000 | | LOG_LEVEL | Log level (debug, info, warn, error) | info | | LOG_DESTINATION | Log destination (stdout, stderr, file, none) | stderr (for stdio transport), stdout (for http transports) | | LOG_FILE | Path to log file (when LOG_DESTINATION is file) | (none) | | DEBUG | Enable debug mode (true/false) | false | | V8_AUTH_API_ENDPOINT | Authentication API endpoint URL | (none) | | V8_AUTH_REQUIRE | Require authentication for API endpoints | 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) | | FAL_KEY | fal.ai API key for asset generation | (required) | | BLOCKADE_LABS_API_KEY | Blockade Labs API key for skybox generation | (required for skybox generation) | | V8_CREDIT_CLIENT_ID | Client ID for credit consumption API | (none, optional for asset generation) | | V8_CREDIT_CLIENT_SECRET | Client secret for credit consumption API | (none, optional for asset generation) | | V8_CREDIT_API_ENDPOINT | API endpoint for credit consumption | (required for asset generation) | | ENABLE_ALL_TOOLS | Enable or disable all tools globally | true | | ENABLE_VECTOR_SEARCH_TOOLS | Enable or disable all vector search tools | true | | ENABLE_ASSET_GENERATE_TOOLS | Enable or disable all asset generation tools (images, cinematics, audio, skyboxes) | true | | ENABLE_IMAGE_GENERATION_TOOLS | Enable or disable image generation tools | true | | ENABLE_CINEMATIC_GENERATION_TOOLS | Enable or disable cinematic generation tools | true | | ENABLE_AUDIO_GENERATION_TOOLS | Enable or disable audio generation tools | true | | ENABLE_SKYBOX_GENERATION_TOOLS | Enable or disable skybox generation tools | true | | ENABLE_CODE_EXAMPLE_SEARCH_TOOL | Enable or disable code example search tool | true | | ENABLE_GAME_RESOURCE_SEARCH_TOOL | Enable or disable game resource search tool | true | | ENABLE_UI_THEME_TOOLS | Enable or disable UI theme tool | true |

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

  1. Individual tool settings (e.g., ENABLE_CODE_EXAMPLE_SEARCH_TOOL)
  2. Asset type settings (e.g., ENABLE_IMAGE_GENERATION_TOOLS, ENABLE_CINEMATIC_GENERATION_TOOLS)
  3. Tool group settings (e.g., ENABLE_VECTOR_SEARCH_TOOLS, ENABLE_ASSET_GENERATE_TOOLS)
  4. Global tool setting (ENABLE_ALL_TOOLS)

Individual settings always override group settings, and group settings override the global setting. When individual settings are explicitly set, they take precedence over their parent settings.

Important: To enable only specific tools, you should set all higher-level settings to false and only enable the specific tools you need. This approach provides a more consistent and predictable configuration.

Examples:

# Enable only vector search tools
ENABLE_ALL_TOOLS=false
ENABLE_VECTOR_SEARCH_TOOLS=true

# Enable only image generation tool, disable all others
ENABLE_ALL_TOOLS=false
ENABLE_ASSET_GENERATE_TOOLS=false
ENABLE_IMAGE_GENERATION_TOOLS=true

# Enable only code example search tool, disable all others
ENABLE_ALL_TOOLS=false
ENABLE_VECTOR_SEARCH_TOOLS=false
ENABLE_CODE_EXAMPLE_SEARCH_TOOL=true

# Enable only cinematic and audio generation tools
ENABLE_ALL_TOOLS=false
ENABLE_ASSET_GENERATE_TOOLS=false
ENABLE_CINEMATIC_GENERATION_TOOLS=true
ENABLE_AUDIO_GENERATION_TOOLS=true

Using Single Transport

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

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

# Build and run with streamable-http transport (default port: 3000)
pnpm build
pnpm start --transports=streamable-http --port=3000

Using Multiple Transports

# Build and run with both SSE and streamable-http transports on the same port
pnpm build
pnpm start --transports=sse,streamable-http --port=3000

# Build and run with all transports (stdio + http-based transports)
pnpm build
pnpm start --transports=stdio,sse,streamable-http --port=3000

Using Environment Variables for Multiple Transports

# Set environment variables
export MCP_TRANSPORTS=sse,streamable-http
export PORT=3000

# Run the server
pnpm start

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

help

运行方式说明

cloud

托管运行

托管运行通常表示这个 MCP Server 由服务方环境承载,用户一般按页面提供的连接方式或授权流程接入,不需要在本地长期启动一个 MCP 进程

  1. 打开服务方连接页
  2. 完成授权或复制端点
  3. 在 MCP 客户端中连接
terminal

本地运行 / 其它方式

本地运行通常需要用户在自己的电脑或服务器上安装依赖,把 server_config 复制到 MCP 客户端,并按 env_schema 补齐环境变量、密钥或其它配置

  1. 复制 server_config
  2. 安装所需依赖
  3. 补齐环境变量后重启客户端