# Steam Review

> Use this tool when you need to analyze Steam game reviews and player sentiment, or fetch game details from the Steam Store API. It solves problems related to understanding player feedback, identifying game strengths and weaknesses, and tracking changes in player sentiment over time. The tool takes in customizable parameters such as language and review type, and outputs cleaned and formatted review text for compatibility with various LLM models.

Canonical page: https://skillsregistry.net/skills/fenxer-steam-review  
JSON: https://api.skillsregistry.net/v1/skills/fenxer-steam-review

## Description

Steam Review MCP provides AI assistants with access to Steam game reviews and information through a Node.js server implementation. It offers tools to fetch game reviews with customizable parameters (language, filter type, review type) and game details from the Steam Store API, along with pre-built prompts for summarizing reviews and analyzing recent player sentiment. The implementation cleans and formats review text for compatibility with various LLM models, making it particularly valuable for understanding player feedback, identifying game strengths and weaknesses, and tracking changes in player sentiment over time.

## Trust

- **Trust score (0–1):** 0.99
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-09-28

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/fenxer-steam-review)
- **Repository:** <https://github.com/fenxer/steam-review-mcp>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "fenxer-steam-review"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/fenxer-steam-review` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/fenxer-steam-review/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt