# Steam Review MCP

> Use this tool when you need to analyze Steam game reviews and gather insights on player opinions. It retrieves review statistics, game information, and summarizes pros and cons, helping you make informed decisions about games. Ideal for use cases such as game research, recommendation systems, and market analysis, this tool accepts game names or IDs as input and outputs detailed review analysis and summaries.

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

## Description

Enables LLMs to retrieve and analyze Steam game reviews, providing access to review statistics, game information, and helping summarize pros and cons of games.

## Trust

- **Trust score (0–1):** 0.99
- **Verification tier:** verified
- **Last scanned:** 2026-09-19

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-09-19

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/qm6v81zpb4)
- **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-mcp"
    }
  }
}
```

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