# WildberriesToolsMCP

> Use this tool when you need to retrieve and analyze Wildberries product reviews in a structured format. It solves the problem of collecting and processing large amounts of review data by providing a server that fetches reviews and outputs them as JSON, making it suitable for Large Language Model (LLM) analysis. Ideal for use cases requiring sentiment analysis, review summarization, or opinion mining in e-commerce applications.

Canonical page: https://skillsregistry.net/skills/happyfunnysad-wildberriestoolsmcp  
JSON: https://api.skillsregistry.net/v1/skills/happyfunnysad-wildberriestoolsmcp

## Description

MCP server for retrieving Wildberries product reviews and formatting them as JSON for LLM analysis.

## Trust

- **Trust score (0–1):** 0.67
- **Verification tier:** scanned
- **Last scanned:** 2026-08-31

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-08-31

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/vufu52rmi6)
- **Repository:** <https://github.com/Happyfunnysad/WildberriesToolsMCP>

## 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": "happyfunnysad-wildberriestoolsmcp"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/happyfunnysad-wildberriestoolsmcp` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/happyfunnysad-wildberriestoolsmcp/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