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PlayTonight MCP Server

@timhosey

代码仓库

基本信息

分类

其他

传输方式

stdio

作者

timhosey

关于 PlayTonight MCP Server

PlayTonight is an MCP server for enabling querying of your game library with a LLM for casual suggestions calculated in an intelligent way.

#playtonight#game-suggestions#llm-querying

PlayTonight MCP Server 配置

暂无标准配置

该服务器的 README 中没有可解析的 MCP 配置块，请前往代码仓库查看安装说明。

代码仓库

PlayTonight MCP Server 工具

工具列表暂未提供

当前收录暂时没有可展示的工具列表，不代表服务没有工具。请查阅项目文档了解支持的能力。

工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。

概览

What is PlayTonight?

PlayTonight is an MCP server that enables querying your game library with a large language model for casual, intelligently calculated game suggestions.

How to use PlayTonight?

Configure the tool in Open-WebUI (configuration steps are not yet provided), then set the supplied system prompt. Use the /refine command to extract relevant keywords from the user’s conversational message, then pass those keywords to /recommend to get game suggestions. Always prioritize the user’s stated preferences over random selection.

Key features of PlayTonight

  • Queries your personal game library for suggestions
  • Uses /refine and /recommend commands for interaction
  • Prioritizes user-stated preferences like genre, mood, or setting
  • Returns playtime in minutes (should be converted to hours when displayed)
  • Only suggests games returned by the tool server

Use cases of PlayTonight

  • Decide what to play tonight based on current mood or genre interest
  • Find a game from your library that matches a specific setting or theme
  • Get a quick, intelligent recommendation when you can’t choose

常见问题

1

What is PlayTonight?

PlayTonight is an MCP server that lets you query your game library with an LLM for casual, intelligent game recommendations.

2

What commands does PlayTonight use?

PlayTonight uses `/refine` to extract keywords from the user’s message and `/recommend` to return game suggestions based on those keywords.

3

How should playtime be presented to the user?

Playtime is returned in minutes; the LLM should convert it to hours when presenting the information to the user.

4

What should the LLM prioritize when making recommendations?

The LLM should prioritize the user’s stated preferences (e.g., genre, mood, setting). Random selection should be used only if no preferences are given.

5

Can the LLM suggest games not returned by PlayTonight?

No. The LLM must only suggest games that were returned by the tool server and must not invent responses.

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