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dsers-mcp-product-py

dsers-mcp-product-py is a skill for Claude Code, Codex from PrathamITHub/dsers-mcp-product-py. It costs 64 tokens per session (1,524 once invoked), scanned A, original, MIT.

A product-import workflow for DSers, a dropshipping service that moves products from marketplaces such as AliExpress, Alibaba, or 1688 into online stores. The Python version prepares, previews, and pushes products to Shopify, Wix, or WooCommerce.

In plain words
What is it for?
Use it to import products from marketplace URLs, edit them with store rules, preview the result, choose whether they are visible, push them to one or more stores, and check the import job status.
Why use it?
It puts rule discovery, preview, confirmation, and result checking into a defined order. It helps reduce mistakes when applying store, shipping, pricing, or visibility rules to one or many products.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: positional $N argument.

not rated 2repo 2d ago A scan 64 tokens original MIT

Good fit Use it to import products from marketplace URLs, edit them with store rules, preview the result, choose whether they are visible, push them to one or more stores, and check the import job status.

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Install with agentmods
npx agentmods add skills/prathamithub/dsers-mcp-product-py/dsers-mcp-product-py
View source ↗ PrathamITHub/dsers-mcp-product-py
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add PrathamITHub/dsers-mcp-product-py --skill dsers-mcp-product-py
Clone the repo
git clone --depth 1 https://github.com/PrathamITHub/dsers-mcp-product-py

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for dsers-mcp-product-py

README.md
[![agentmods](https://agentmods.dev/badge/skills/prathamithub/dsers-mcp-product-py/dsers-mcp-product-py/github.svg)](https://agentmods.dev/skills/prathamithub/dsers-mcp-product-py/dsers-mcp-product-py)
Your own site
<a href="https://agentmods.dev/skills/prathamithub/dsers-mcp-product-py/dsers-mcp-product-py"><img src="https://agentmods.dev/badge/skills/prathamithub/dsers-mcp-product-py/dsers-mcp-product-py/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for dsers-mcp-product-py

Your own site · 80×15
<a href="https://agentmods.dev/skills/prathamithub/dsers-mcp-product-py/dsers-mcp-product-py"><img src="https://agentmods.dev/badge/skills/prathamithub/dsers-mcp-product-py/dsers-mcp-product-py.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 64 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,524 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00064 $0.01524
Opus 5 $0.00032 $0.00762
Sonnet 5 $0.00013 $0.00305
Haiku 4.5 $0.00006 $0.00152

Measured 11d ago against content hash 97aa2cf99368, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

dsers-mcp-product-py scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

SKILL.md · 140 lines

How it starts

The opening of the file, as written. The whole thing — 140 lines — stays where its author put it; the contents beside it link to each section on GitHub.

DSers MCP Product (Python)

Workflow

Always follow this order:

  1. get_rule_capabilities — discover stores, shipping profiles, supported rules
  2. validate_rules — (optional) dry-run rule validation before importing
  3. prepare_import_candidate — import from URL(s), apply rules, get preview with job_id
  4. get_import_preview — (optional) reload a saved preview
  5. set_product_visibility — (optional) toggle backend_only / sell_immediately
  6. confirm_push_to_store — push to store(s)
  7. get_job_status — verify push result

Step 1 is required before any import — it returns the store list, shipping profiles, and rule constraints.

Key Decisions

Single vs Batch

  • User gives one URL → use source_url in prepare_import_candidate
  • User gives multiple URLs → use source_urls (array). Each URL is processed independently; failures don't block others.
  • Mixed sources (AliExpress + 1688 + Alibaba) work in the same batch call.

Push Modes

  • Single: job_id + target_store
  • Batch: job_ids (array) + target_store
  • Multi-store: job_id + target_stores (array)
  • Batch + multi-store: job_ids + target_stores → N jobs x M stores

Shopify Shipping Profile

The system auto-discovers delivery profiles for Shopify stores. No manual GIDs needed.

  • Default behavior: picks the profile marked as default in DSers
  • To use a specific profile: set push_options.shipping_profile_name (e.g. "DSers Shipping Profile")
  • get_rule_capabilities returns shipping_profiles per Shopify store — show these to the user if they ask

Non-Shopify stores (Wix, WooCommerce) skip shipping profile entirely.

Rules

Rules are applied at prepare_import_candidate time and frozen into the job. They do NOT change at push time.

  • pricing: mode (provider_default, multiplier, fixed_markup), multiplier, fixed_markup, round_digits
  • content: title_prefix, title_suffix, title_override, description_override_html, description_append_html, tags_add
  • images: keep_first_n, drop_indexes

Read the full file on GitHub · 140 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 11d ago First seen · 140 lines · 64 tokens per session scan A 97aa2cf99368

Subscribe to this mod's changes

dsers-mcp-product-py is a skill published in the GitHub repository PrathamITHub/dsers-mcp-product-py (2 stars, last pushed 2d ago), licensed MIT. It adds 64 tokens to every session and 1,524 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

E-commerceai-agentaliexpressdropshippingdsersmcpmcp-server
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