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PCDCK/ozon-mcp

PCDCK/ozon-mcp

Ozon Seller and Performance APIs with auto-pagina
在 GitHub 查看 ↗直链 · 无中转页
配置模板(请按你的客户端调整)
claude mcp add ozon-mcp -- npx -y ozon-mcp
这是根据仓库名生成的可粘贴骨架,命令行参数与包名请以该项目 README 为准。
★ 数取值
23 ★ · PCDCK/ozon-mcp · 取自该仓库的 GitHub 页面 · (2026-10-16 20:00:20 核对)
来源明细
收录自 punkpeye/awesome-mcp-servers 榜单(我们从中收集的条目之一) · 条目类型:MCP 服务
收录与活跃
收录于 2026-10-09 · 最近见到 2026-10-16 · 共见到 32 次 · 被 7 个来源列出
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综合分 703 · 23 ★ · 7 个来源 · mcp
常见问题(答案都来自我们的记录)
怎么安装?
我们【没有】从该仓库取到安装命令(我们的 install 覆盖率只有约 4%)。请看它的 README 或 releases 页。
它适合谁 / 用来做什么?
我们把它归在这些标签下: MCP 服务。标签来自条目自身,不是我们强加的分类。
谁维护它、还在更新吗?
仓库 PCDCK/ozon-mcp;我们收录于 2026-10-09;最近见到 2026-10-16。这里没有"官方认证"或"质量评级"——我们只记录来源与时间。
第三方质量标记

ozon-mcp

以下摘录自该仓库的 README(片段) · 在 GitHub 读完整 README →

> MCP server for the Ozon Seller & Performance APIs.
> Connect any AI agent to your Ozon cabinet in minutes.
ozon-mcp is a knowledge-rich MCP server that turns the entire Ozon
seller toolkit into 15 high-leverage tools. AI agents (Claude, Cursor,
Cline, Continue, Goose, Zed, …) can search the API in Russian or
English, drill into any of 466 methods with a fully-resolved JSON
Schema, and execute calls with built-in safety guards. Subscription-
aware, automatic pagination over all 4 cursor styles, retry/back-off
on 429s, and 13 ready-to-use analytical workflows.
**Key facts:** 466 indexed methods (420 Seller + 46 Performance),
55 sections, 5 subscription tiers modelled, 38 paginated endpoints
auto-walked, 43 destructive methods double-gated, 13 curated
workflows for typical seller scenarios.
---
Quick start
Prerequisites
- Python 3.12 or 3.13
- uv package manager — install with
curl -LsSf https://astral.sh/uv/install.sh | sh
- Ozon Seller API credentials (Client-Id + Api-Key) — get them at
Installation
Verify it works
You should see the FastMCP usage line. The server speaks the MCP stdio
protocol — point any compatible client at it (instructions below).
---
Connecting to your AI agent
ozon-mcp uses the standard MCP stdio transport. Every example below
exposes the same 15 tools — pick whichever client you already use.
Claude Desktop
Edit:
~/Library/Application Support/Claude/claude_desktop_config.json
(macOS) or %APPDATA%\Claude\claude_desktop_config.json (Windows).
Claude Code (CLI)
Or add to ~/.claude/mcp.json with the same shape as the Claude
Desktop config above.
Cursor
Settings → MCP → Add new MCP Server, or edit ~/.cursor/mcp.json:
Windsurf
Edit ~/.codeium/windsurf/mcp_config.json:
Cline (VS Code extension)
Cline → Settings → MCP Servers → Add:
Continue.dev
Edit ~/.continue/config.json:
Goose, Zed, or any other MCP client
Any client that speaks MCP stdio will work. Generic config:
Browse the official MCP client list at
.
---
Usage examples
All examples below show realistic responses copied from
tests/fixtures/responses/ — anonymized
identifiers (99000001, TEST-SKU-001) but real shape.
Example 1 — Get all your products
> **You:** Use ozon_fetch_all with operation_id="ProductAPI_GetProductList"
> to get all my products.
The agent calls:
Server walks the last_id cursor automatically and returns:
Example 2 — Find products at risk of going out of stock
> **You:** Run the oos_risk_analysis workflow for my cabinet.
Agent first inspects the workflow:
→ tells the agent to call AnalyticsAPI_StocksTurnover (rate-limited
to 1 req/min — the server's per-endpoint queue handles that for you)
and how to interpret turnover_grade. The call returns:
The workflow's interpret field tells the agent to flag SKUs where
idc **You:** Check the health of my Ozon cabinet using the
> cabinet_health_check workflow.
The workflow tells the agent to read three endpoints in parallel —
RatingAPI_RatingSummaryV1, SellerAPI_SellerInfo,
AverageDeliveryTimeSummary. The first call returns:
Example 4 — Analyze product pricing
> **You:** Which of my products have a red price index?
Agent runs the pricing_analysis workflow and inspects the
price_indexes.color_index field on every item:
The workflow's common_mistakes list reminds the agent to compare
against marketing_seller_price (the actual buyer-facing price), not
just the base price.
Example 5 — Content audit
> **You:** Find products with low content rating and tell me what to
> improve.
Agent runs content_audit, gets per-SKU ratings + the list of
attributes that would lift the score:
来源
awesome · https://github.com/PCDCK/ozon-mcp
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