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steam

by dsp
GitHub
MIT License
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Integrations

  • Provides Steam gaming context to AI assistants by integrating with the Steam API to fetch user gaming information, allowing AI assistants to access and understand users' gaming activities and preferences

MCP Steam Server

A Model Context Protocol (MCP) server that provides Steam gaming context to AI assistants. This service integrates with the Steam API to fetch user gaming information and exposes it through the MCP protocol, allowing AI assistants to access and understand users' gaming activities and preferences.

Installation

The easiest way to run the MCP Steam server is using Docker:

docker run --rm -i ghcr.io/dsp/mcp-server-steam:latest

Configuration

The server can be configured using environment variables:

# Required configuration STEAM_API_KEY=your_steam_api_key

Development

Prerequisites

  • OpenJDK 21
  • Docker (for container builds)
  • Git
  • devenv.sh

Setting Up Development Environment

  1. Clone the repository:
    git clone https://github.com/dsp/mcp-steam.git cd mcp-steam
  2. Use the development shell:
    devshell shell
    This will set up the required development environment with all necessary dependencies.
  3. Build the project:
    mvn package

Building Docker Image Locally

docker build -t mcp-server-steam .

API Documentation

The server implements the Model Context Protocol (MCP) specification. For detailed API documentation, please refer to the MCP Documentation.

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

License

MIT License

This server cannot be installed

-
security - not tested
A
license - permissive license
-
quality - not tested

remote-capable server

The server can be hosted and run remotely because it primarily relies on remote services or has no dependency on the local environment.

Provide information about the games you played and how long you played them for to an LLM

  1. Installation
    1. Using Docker (Recommended)
    2. Configuration
  2. Development
    1. Prerequisites
    2. Setting Up Development Environment
    3. Building Docker Image Locally
  3. API Documentation
    1. Contributing
      1. License

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