
steamstats-mcp
MCP Server for Steam Web API Game Statistics
3 years
Works with Finder
1
Github Watches
0
Github Forks
0
Github Stars
SteamStats MCP Server
Warning
Current implementation is not operational!
Overview
This project implements a SteamStats MCP (Model Context Protocol) Server using Python and FastAPI. The server acts as an intermediary between an MCP client (like Roo) and the Steam Web API, providing structured access to various Steam game statistics and user information.
It exposes a single /message
endpoint that accepts JSON-RPC style tools/call
requests, validates them, interacts with the Steam Web API, and returns formatted results or appropriate error messages.
Technology Stack
- Language: Python 3.11+
- Framework: FastAPI
- Data Validation: Pydantic
- Web Server: Uvicorn
- HTTP Client: Requests
- Package Management: UV
Request Flow
The following diagram illustrates the typical request flow:
sequenceDiagram
participant Client as MCP Client
participant Server as SteamStats MCP Server
participant SteamAPI as Steam Web API
Client->>Server: POST /message (tools/call, command, args)
Server->>Server: Validate MCP message format
alt Invalid Format
Server-->>Client: Error Response (e.g., Invalid Request)
else Valid Format
Server->>Server: Parse command & arguments
Server->>Server: Validate arguments using Pydantic
alt Invalid Arguments
Server-->>Client: Error Response (Validation Error)
else Valid Arguments
Server->>SteamAPI: Make API Request(s) (e.g., GET /ISteamUserStats/...)
SteamAPI-->>Server: API Response (JSON data or error)
alt Steam API Error
Server->>Server: Log API Error
Server-->>Client: Error Response (API Error)
else Successful API Response
Server->>Server: Process API data
Server-->>Client: Success Response (result data)
end
end
end
Setup and Installation
-
Prerequisites:
- Python 3.11 or higher.
-
UV package manager installed (
pip install uv
).
-
Clone the repository (if you haven't already):
git clone <repository-url> cd steamstats_mcp
-
Create a virtual environment (recommended):
# Using uv uv venv source .venv/bin/activate # On Linux/macOS # .venv\Scripts\activate # On Windows # Or using standard venv # python -m venv .venv # source .venv/bin/activate # On Linux/macOS # .venv\Scripts\activate # On Windows
-
Install dependencies:
uv pip install -r requirements.txt # Assuming a requirements.txt exists or will be generated from pyproject.toml # Or directly from pyproject.toml if using uv for management # uv sync
(Note: You might need to generate
requirements.txt
frompyproject.toml
usinguv pip freeze > requirements.txt
if directuv sync
isn't used) -
Configure Environment Variables: See the section below.
Configuration (Environment Variables)
The server requires the following environment variables to be set:
-
STEAM_API_KEY
(Required): Your Steam Web API key. Obtain one from the Steam Developer website. The server will not function without this key. -
LOG_LEVEL
(Optional): Sets the logging level. Options includeDEBUG
,INFO
,WARNING
,ERROR
,CRITICAL
. Defaults toINFO
. -
HOST
(Optional): The host address for the server to bind to. Defaults to0.0.0.0
(listens on all available network interfaces). -
PORT
(Optional): The port for the server to listen on. Defaults to8000
.
You can set these variables in your shell environment, using a .env
file (requires python-dotenv
package and code modification to load it), or through your deployment system's configuration.
Example (Linux/macOS):
export STEAM_API_KEY="YOUR_API_KEY_HERE"
export LOG_LEVEL="DEBUG"
export PORT="8080"
Example (Windows CMD):
set STEAM_API_KEY=YOUR_API_KEY_HERE
set LOG_LEVEL=DEBUG
set PORT=8080
Example (Windows PowerShell):
$env:STEAM_API_KEY = "YOUR_API_KEY_HERE"
$env:LOG_LEVEL = "DEBUG"
$env:PORT = "8080"
Running the Server
Once dependencies are installed and environment variables are configured, run the server using Uvicorn:
uvicorn main:app --host $HOST --port $PORT --reload
- Replace
main:app
if your FastAPI application instance is named differently or located in a different file. - The
--reload
flag enables auto-reloading during development (remove for production). - Uvicorn will use the
HOST
andPORT
environment variables if set, or their defaults (0.0.0.0
and8000
).
The server should now be running and listening for MCP requests on http://<HOST>:<PORT>/message
.
Available MCP Commands
Refer to STEAMSTATS_MCP_SPECIFICATION.md
for detailed information on available commands, their arguments, and expected results. Currently implemented commands include:
-
getCurrentPlayers
-
getAppDetails
-
getGameSchema
-
getGameNews
-
getPlayerAchievements
-
getUserStatsForGame
-
getGlobalStatsForGame
-
getSupportedApiList
-
getAppList
-
getGlobalAchievementPercentages
Connecting a Local MCP Client (e.g., Roo)
To connect a local MCP client, such as the Roo VS Code extension, to this running server, you need to configure the client's mcp.json
file. This file typically resides in a .roo
directory within your project or user settings.
The configuration tells the client how to communicate with the server. Since this is an HTTP-based server (FastAPI/Uvicorn), you'll use the sse
(Server-Sent Events) type.
-
Ensure the SteamStats MCP Server is running: Follow the "Running the Server" instructions above. By default, it runs on
http://localhost:8000
. -
Locate or create your
mcp.json
file: This might be in.roo/mcp.json
in your workspace or a global configuration location. -
Add the server configuration: Add an entry to the
servers
array inmcp.json
.
Example mcp.json
entry:
{
"servers": [
// ... other server configurations ...
{
"name": "steamstats-local", // Choose a descriptive name
"type": "sse",
"enabled": true,
"url": "http://localhost:8000/message", // Adjust host/port if you changed defaults
"readTimeoutSeconds": 60,
"writeTimeoutSeconds": 60
}
]
}
-
name
: A unique identifier for this server connection. -
type
: Must besse
for HTTP-based servers. -
enabled
: Set totrue
to activate the connection. -
url
: The full URL to the/message
endpoint of the running server. Make sure the host and port match how you are running the server (e.g., if you usedexport PORT=8081
, change the URL accordingly). -
readTimeoutSeconds
/writeTimeoutSeconds
: Optional timeouts.
Once configured and the server is running, your MCP client should be able to connect and utilize the tools provided by this SteamStats server.
相关推荐
Converts Figma frames into front-end code for various mobile frameworks.
I find academic articles and books for research and literature reviews.
Confidential guide on numerology and astrology, based of GG33 Public information
Embark on a thrilling diplomatic quest across a galaxy on the brink of war. Navigate complex politics and alien cultures to forge peace and avert catastrophe in this immersive interstellar adventure.
Advanced software engineer GPT that excels through nailing the basics.
Delivers concise Python code and interprets non-English comments
💬 MaxKB is a ready-to-use AI chatbot that integrates Retrieval-Augmented Generation (RAG) pipelines, supports robust workflows, and provides advanced MCP tool-use capabilities.
Micropython I2C-based manipulation of the MCP series GPIO expander, derived from Adafruit_MCP230xx
The all-in-one Desktop & Docker AI application with built-in RAG, AI agents, No-code agent builder, MCP compatibility, and more.
MCP server to provide Figma layout information to AI coding agents like Cursor
Reviews

user_jB3oxTyZ
Steamstats-mcp is an exceptional tool for any serious Steam enthusiast! Developed by algorhythmic, this application provides in-depth statistics and insights on your gaming habits. It's easy to use and incredibly informative, helping me track my game time and achievements in a seamless way. Highly recommended for anyone looking to get the most out of their gaming experience on Steam. Check it out here: https://github.com/algorhythmic/steamstats-mcp