AGS API MCP Server

AGS API MCP Server

Enables AI assistants to interact with AccelByte Gaming Services APIs through semantic search, detailed API information retrieval, and authenticated API execution for game backend operations.

Category
访问服务器

README

AGS API MCP Server

Description

The AGS API MCP Server is a Model Context Protocol (MCP) server that provides AI assistants with access to AccelByte Gaming Services APIs through OpenAPI integration.

What It Is

An MCP server built with TypeScript that bridges AI assistants (VS Code Copilot, Cursor, Claude) with AccelByte Gaming Services APIs. It implements the Model Context Protocol to expose AccelByte APIs as tools that AI assistants can discover and use.

What It's For

Enable AI assistants to interact with AccelByte APIs by:

  • Searching for available AccelByte API operations
  • Getting detailed information about specific APIs
  • Executing API requests with proper authentication
  • Retrieving token information

What It Does

  • Exposes AccelByte APIs as MCP Tools: Provides access to AccelByte APIs through MCP tools
  • Provides Semantic Search: Search across OpenAPI operations by description, tags, or path
  • Executes API Requests: Runs API calls with proper authentication and validation
  • Provides Token Information: Retrieves information about authenticated tokens

Prerequisites

  • Docker installed and running
  • AccelByte Environment URL (AB_BASE_URL) - Your AccelByte environment base URL
  • (Optional) AccelByte OAuth Credentials - If using authentication features

Quick Start

Visual Studio Code

Create or edit .vscode/mcp.json in your workspace (or configure in user settings):

{
  "servers": {
    "ags-api": {
      "type": "stdio",
      "command": "docker",
      "args": [
        "run",
        "--rm",
        "--interactive",
        "--env", "AB_BASE_URL=https://yourgame.accelbyte.io",
        "--env", "OAUTH_CLIENT_ID=your-client-id",
        "--env", "OAUTH_CLIENT_SECRET=your-client-secret",
        "ghcr.io/accelbyte/ags-api-mcp-server:2025.9.0"
      ]
    }
  }
}

Note: Replace the placeholder values with your actual AccelByte credentials. You can also use input variables for sensitive data. See the VS Code MCP documentation for more details.

Location:

  • Workspace: .vscode/mcp.json
  • User settings: VS Code settings UI or settings.json

Cursor

Create or edit .cursor/mcp.json in your workspace (or configure in user settings):

{
  "mcpServers": {
    "ags-api": {
      "command": "docker",
      "args": [
        "run",
        "--rm",
        "--interactive",
        "--env", "AB_BASE_URL=https://yourgame.accelbyte.io",
        "--env", "OAUTH_CLIENT_ID=your-client-id",
        "--env", "OAUTH_CLIENT_SECRET=your-client-secret",
        "ghcr.io/accelbyte/ags-api-mcp-server:2025.9.0"
      ]
    }
  }
}

Note: Replace the placeholder values with your actual AccelByte credentials. See the Cursor MCP documentation for more details.

Location:

  • Workspace: .cursor/mcp.json
  • User settings: Cursor settings UI

Claude Desktop

Edit your Claude Desktop configuration file:

macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
Windows: %APPDATA%\Claude\claude_desktop_config.json

{
  "mcpServers": {
    "ags-api": {
      "command": "docker",
      "args": [
        "run",
        "--rm",
        "--interactive",
        "--env", "AB_BASE_URL=https://yourgame.accelbyte.io",
        "--env", "OAUTH_CLIENT_ID=your-client-id",
        "--env", "OAUTH_CLIENT_SECRET=your-client-secret",
        "ghcr.io/accelbyte/ags-api-mcp-server:2025.9.0"
      ]
    }
  }
}

Note: Replace the placeholder values with your actual AccelByte credentials. See the Claude Desktop MCP documentation for more details.

After configuration: Restart your AI assistant application to load the MCP server.

Claude Code

Claude Code uses a different configuration system than Claude Desktop. You can configure MCP servers either via CLI command or by creating a .mcp.json file.

Option 1: Using CLI Command

Run the following command in your terminal:

claude mcp add --transport stdio ags-api -- \
  docker run --rm --interactive \
  --env AB_BASE_URL=https://yourgame.accelbyte.io \
  --env OAUTH_CLIENT_ID=your-client-id \
  --env OAUTH_CLIENT_SECRET=your-client-secret \
  ghcr.io/accelbyte/ags-api-mcp-server:2025.9.0

Note: Replace the placeholder values with your actual AccelByte credentials. The -- separator is required to distinguish Claude CLI flags from the Docker command.

Option 2: Using .mcp.json File

Create or edit .mcp.json in your project root:

{
  "mcpServers": {
    "ags-api": {
      "type": "stdio",
      "command": "docker",
      "args": [
        "run",
        "--rm",
        "--interactive",
        "--env", "AB_BASE_URL=https://yourgame.accelbyte.io",
        "--env", "OAUTH_CLIENT_ID=your-client-id",
        "--env", "OAUTH_CLIENT_SECRET=your-client-secret",
        "ghcr.io/accelbyte/ags-api-mcp-server:2025.9.0"
      ]
    }
  }
}

Note: Replace the placeholder values with your actual AccelByte credentials. See the Claude Code MCP documentation for more details.

Location: .mcp.json in your project root directory

Antigravity

Antigravity uses mcp_config.json for MCP server configuration. Create or edit the configuration file:

Location: mcp_config.json in your project root

{
  "mcpServers": {
    "ags-api": {
      "command": "docker",
      "args": [
        "run",
        "--rm",
        "--interactive",
        "--env", "AB_BASE_URL=https://yourgame.accelbyte.io",
        "--env", "OAUTH_CLIENT_ID=your-client-id",
        "--env", "OAUTH_CLIENT_SECRET=your-client-secret",
        "ghcr.io/accelbyte/ags-api-mcp-server:2025.9.0"
      ]
    }
  }
}

Note: Replace the placeholder values with your actual AccelByte credentials. See the Antigravity MCP documentation for more details.

Location: mcp_config.json in your project root directory

Gemini CLI

Gemini CLI uses a different configuration system. You can configure MCP servers either via CLI command or by editing settings.json.

Option 1: Using CLI Command

Run the following command in your terminal:

gemini mcp add --transport stdio --env AB_BASE_URL=https://yourgame.accelbyte.io --env OAUTH_CLIENT_ID=your-client-id --env OAUTH_CLIENT_SECRET=your-client-secret ags-api -- docker run --rm --interactive ghcr.io/accelbyte/ags-api-mcp-server:2025.9.0

Note: Replace the placeholder values with your actual AccelByte credentials. The -- separator is required to distinguish Gemini CLI flags from the Docker command. See the Gemini CLI MCP documentation for more details.

Option 2: Using settings.json File

Edit your Gemini CLI settings file:

User scope: ~/.gemini/settings.json
Project scope: .gemini/settings.json (in your project root)

{
  "mcpServers": {
    "ags-api": {
      "command": "docker",
      "args": [
        "run",
        "--rm",
        "--interactive",
        "--env", "AB_BASE_URL=https://yourgame.accelbyte.io",
        "--env", "OAUTH_CLIENT_ID=your-client-id",
        "--env", "OAUTH_CLIENT_SECRET=your-client-secret",
        "ghcr.io/accelbyte/ags-api-mcp-server:2025.9.0"
      ]
    }
  }
}

Note: Replace the placeholder values with your actual AccelByte credentials. See the Gemini CLI MCP documentation for more details.

Location:

  • User scope: ~/.gemini/settings.json
  • Project scope: .gemini/settings.json in your project root

Using the Tools

Once configured, your AI assistant can use the following MCP tools to interact with AccelByte APIs:

get_token_info

Get information about the authenticated user and token (if available). Returns details such as:

  • User ID and display name
  • Namespace
  • Roles and permissions
  • Token expiration information

Example usage: Ask your AI assistant "What's my current user information?" or "Show me my token details".

search-apis

Search for AccelByte API operations by:

  • Description or summary text
  • HTTP method (GET, POST, PUT, DELETE, etc.)
  • API tags
  • Service name

Example usage: "Find APIs for user management" or "Search for inventory-related endpoints".

describe-apis

Get detailed information about a specific API operation, including:

  • Request parameters and schemas
  • Response schemas
  • Authentication requirements
  • Example requests

Example usage: "Show me details about the getUserProfile API" or "What parameters does the createItem endpoint need?".

run-apis

Execute API requests against AccelByte endpoints. The server handles:

  • Authentication with your token
  • Request validation
  • Response formatting

Note: For write operations (POST, PUT, PATCH, DELETE), the server may request your consent before executing.

Example usage: "Get my user profile" or "List all items in my inventory".

Workflow Support

The server also provides workflow resources and prompts for running predefined workflows. Ask your AI assistant about available workflows or use the run-workflow prompt.

Bonus: Running Docker Container Manually

If you prefer to run the Docker container manually instead of configuring it through your AI assistant's MCP configuration files:

Run the Container

docker run -d \
  --name ags-api-mcp-server \
  -e AB_BASE_URL=https://yourgame.accelbyte.io \
  -e OAUTH_CLIENT_ID=your-client-id \
  -e OAUTH_CLIENT_SECRET=your-client-secret \
  -p 3000:3000 \
  ghcr.io/accelbyte/ags-api-mcp-server:2025.9.0

Note: Replace the placeholder values with your actual AccelByte credentials.

The server will be available at http://localhost:3000/mcp, which you can then add in your VS Code, Cursor, Claude Code, Gemini CLI, or Antigravity configuration.

Configure Your AI Assistant to Use the Running Container

Visual Studio Code

Add to .vscode/mcp.json:

{
  "servers": {
    "ags-api": { "type": "http", "url": "http://localhost:3000/mcp" }
  }
}

Cursor

Add to .cursor/mcp.json:

{
  "mcpServers": {
    "ags-api": { "type": "http", "url": "http://localhost:3000/mcp" }
  }
}

Claude Code

Claude Code uses a different configuration system than Claude Desktop. You can configure MCP servers either via CLI command or by creating a .mcp.json file.

Option 1: Using CLI Command

Run the following command in your terminal:

claude mcp add --transport http ags-api http://localhost:3000/mcp
Option 2: Using .mcp.json File

Create or edit .mcp.json in your project root:

{
  "mcpServers": {
    "ags-api": { "type": "http", "url": "http://localhost:3000/mcp" }
  }
}

Location: .mcp.json in your project root directory

Gemini CLI

Gemini CLI uses a different configuration system. You can configure MCP servers either via CLI command or by editing settings.json.

Option 1: Using CLI Command

Run the following command in your terminal:

gemini mcp add --transport http ags-api http://localhost:3000/mcp
Option 2: Using settings.json File

Edit your Gemini CLI settings file:

User scope: ~/.gemini/settings.json
Project scope: .gemini/settings.json (in your project root)

{
  "mcpServers": {
    "ags-api": { "type": "http", "url": "http://localhost:3000/mcp" }
  }
}

Location:

  • User scope: ~/.gemini/settings.json
  • Project scope: .gemini/settings.json in your project root

Antigravity

Add to mcp_config.json:

{
  "mcpServers": {
    "ags-api": { "type": "http", "url": "http://localhost:3000/mcp" }
  }
}

Documentation

For detailed documentation, see:

Support

For issues and questions, please open an issue in the repository.

推荐服务器

Baidu Map

Baidu Map

百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。

官方
精选
JavaScript
Playwright MCP Server

Playwright MCP Server

一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。

官方
精选
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。

官方
精选
本地
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。

官方
精选
本地
TypeScript
VeyraX

VeyraX

一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。

官方
精选
本地
graphlit-mcp-server

graphlit-mcp-server

模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。

官方
精选
TypeScript
Kagi MCP Server

Kagi MCP Server

一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。

官方
精选
Python
e2b-mcp-server

e2b-mcp-server

使用 MCP 通过 e2b 运行代码。

官方
精选
Neon MCP Server

Neon MCP Server

用于与 Neon 管理 API 和数据库交互的 MCP 服务器

官方
精选
Exa MCP Server

Exa MCP Server

模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。

官方
精选