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ru-marketplace-mcp
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ru-marketplace-mcp

Active·★ 91·MIT·Updated 2026-09-10
★ Trending★ Hidden Gem

This project provides MCP (Model Context Protocol) servers designed for scraping data from major Russian and Chinese e-commerce marketplaces like Wildberries, Ozon, Yandex Market, and Taobao. It allows users to extract product prices, stock, ratings, reviews, and seller information, offering a unified API for price comparison across all supported platforms.

ru-marketplace-mcp is currently grouped under Data Processing, which makes it easier to evaluate through workflow fit instead of isolated features alone. Based on the available data, it leans most heavily toward Read prices, stock, ratings, reviews, and seller identity from multiple Russian and Chinese marketplaces. and Price monitoring and competitive analysis across multiple e-commerce platforms.. The listed license is MIT, which is useful when adoption constraints matter. It also shows measurable community traction with 91 GitHub stars.

#Marketplace Scraping#E-commerce Data#Price Comparison#LLM Tooling#Python#Browser Automation#Data Extraction
$ Install
$ git clone https://github.com/Vladimir-Human/ru-marketplace-mcp.git && cd ru-marketplace-mcp && uv sync --all-packages
↗ Visit site★ GitHub
01

Features

01Read prices, stock, ratings, reviews, and seller identity from multiple Russian and Chinese marketplaces.
02Unified price comparison tool across all supported sources with ranking capabilities.
03Supports both anonymous HTTP requests and browser-based scraping (via Chrome CDP) for robust anti-bot measures.
04Provides detailed product information, including buyer questions, seller answers, and seller legal entity details.
05Offers dedicated tools for each marketplace, enabling targeted and platform-specific data extraction.
02

Why choose it

+Read prices, stock, ratings, reviews, and seller identity from multiple Russian and Chinese marketplaces.
+Price monitoring and competitive analysis across multiple e-commerce platforms.
+Covers 5 supported environments or platforms, which is helpful for broader deployment needs.
+Ships with a public repository and a MIT license, which makes adoption and review easier.
03

Trade-offs

!There are at least 8 related tools in the same category, so the best choice is easier to make after side-by-side comparison.
04

Compatibility

Python
Runtime
Verified via docs
Model Context Protocol (MCP)
Protocol
Verified via docs
Google Chrome (CDP)
Browser
Verified via docs
uv
Package Manager
Verified via docs
LLM Clients (Claude, Cursor)
Integration
Verified via docs
05

Quick start

1
$ git clone https://github.com/Vladimir-Human/ru-marketplace-mcp.git
2
$ cd ru-marketplace-mcp
3
$ uv sync --all-packages
06

Use cases

↳Price monitoring and competitive analysis across multiple e-commerce platforms.
↳Gathering product reviews and buyer questions for market research or sentiment analysis.
↳Verifying seller identity and legal information for due diligence or supplier assessment.
↳Developing LLM-powered agents that require real-time e-commerce data access and interaction.
↳Tracking product availability and stock levels in online and offline stores (e.g., Detsky Mir).
07

How it compares

≈ru-marketplace-mcp sits in the Data Processing category, so it makes more sense to evaluate it alongside tools like mirascope instead of in isolation.
≈If your main need is closer to "Price monitoring and competitive analysis across multiple e-commerce platforms.", that use case is a better lens for comparison than broad feature checklists alone.
≈ru-marketplace-mcp uses a MIT license, and community traction are both easier to judge in category context.
08

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ru-marketplace-mcp AlternativesBest Data Processing Tools 2026Open Source Data Processingru-marketplace-mcp Tutorialru-marketplace-mcp Vs CompetitorsMarketplace ScrapingE-commerce DataPrice Comparison

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On this page
01Features02Why choose it03Trade-offs04Compatibility05Quick start06Use cases07How it compares08Alternatives
Stats
GitHub Stars★ 91
Last commit1d ago
StatusActive
LicenseMIT
CategoryData Processing
Trend (30d)
+3.6↑ 1.5%
Links
Documentation↗Discussion↗Issues↗Releases↗

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