MCP.Market

scrapewright MCP server

online · 100% uptime
by Ozymandias-Owens-2·io.github.Ozymandias-Owens-2/scrapewright·v1.0.3·1 stars
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Give it a URL, get structured rows. A model writes the parser once; replays are free.

A91/100grade A
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Safety scan
A91/100

full report

Adoption
Growing

1 stars82 downloads/wk

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scrapewright tools (5)

write = sends, deletes, buys or posts
  • accountFree

    Credits left and this month's usage for the key in use.

  • crawl_siteFree

    Walk a site and extract every item. Waits up to four minutes; a longer crawl returns a job_id to pass to crawl_status. `mode` picks how the items are found. "rows" (the default) reads every card on the listing itself and follows its pagination -- right for search results, categories and tables. "links" follows each card into its own page, for sites where an item has one. "like" starts from one example item page, given as `like_page`, and finds every other page shaped like it; pass `listing_url` as well when you know the stock or results page, because inferring it is the part that fails.

  • crawl_statusFree

    Fetch a crawl that outlived its call.

  • detect_siteFree

    Report what platform a site runs on and which strategy to use. Cheap; call it before a large job.

  • extract_pageFree

    Extract structured data from ONE page. ``fields`` declares your own schema, e.g. ["title", "salary:number", "tags:list"]; omit it for the product schema. First call on a new site compiles a recipe (300 credits); later calls replay it for 1 credit per row. A site nobody could read is remembered for a week and answered without calling the model, so re-reading a dead page costs nothing. `retry` asks anyway.

Public scan report

scanner v0.1.10 · 2026-10-16 · same rubric, same numbers if you re-run it

no findings
  • Code scan37 source files scanned25/25
  • Live reliabilityremote reachable in 1236ms20/20
  • Tool poisoning5 tool descriptions checked15/15
  • Auth qualityAPI key sent as a header8/15
  • Maintenancelast push 1 days ago15/15
  • Maintainer identityregistry namespace matches repository owner; GitHub account older than a year8/10
Overall 91/100. Components that don't apply are left out of the denominator. Any critical finding is an F.RubricAppeal a findingJSON

How scrapewright compares

Against every graded AI and agents MCP server, from our own scans and uptime checks. Updated after each scan run.

Safety score
91/100
higher than 88% of 4,461 AI and agents servers
Tools
5
the typical AI and agents server has 6
Tools that change things
0%
typical: 0%. Fewer write tools means less an agent can break
Uptime
100%
of our recent checks; the typical remote AI and agents server answers 100%
Response time
367 ms
faster than 40% of 2,334 AI and agents servers
GitHub stars
1
more than 50% of 2,713 AI and agents servers
Downloads a week
82
more than 57% of 1,554 AI and agents servers with a package

What its tools let an agent do: 5 read

Release history: 3 versions in the registry since 2026-09-03, latest 2026-09-29, typically one every 17 days.

Install scrapewright in Claude Code, Cursor or VS Code

claude mcp add --transport http scrapewright https://scrapewright.app/mcp
Add to Cursor

What the publisher says

From the scrapewright repository's README, as published. We do not edit it. Read it on GitHub

scrapewright

Give it a URL. It writes the scraper.

Most e-commerce catalog scraping splits into two worlds: sites on a known platform (Shopify, WooCommerce) that expose a clean JSON feed, and everything else — bespoke HTML where you hand-write a parser per site and re-write it every time the markup shifts. scrapewright collapses both into one call:

API — free, stable, no LLM.

  1. Detect the platform behind a URL.
  2. For known platforms, extract deterministically from their public catalog

it, and replay it deterministically forever after.

  1. For custom HTML, synthesize a reusable extractor once with an LLM, cache

The LLM is a compiler, not a runtime. It runs once per site to produce a recipe of CSS selectors; every page after that is parsed by plain BeautifulSoup at zero marginal cost. That is the whole cost-control story — no per-page model calls, no token bill that scales with your crawl.

┌─────────────┐
   store URL  ───▶  │   detect    │
                    └──────┬──────┘
        ┌──────────────────┼──────────────────┐
        ▼                  ▼                   ▼
    shopify            woocommerce         generic HTML
   products.json      wc/store/products    (page mode)
        │                  │                   │
        │  deterministic   │                   ▼
        │  (free)          │            cached recipe? ──yes──▶ replay (free)
        └────────┬─────────┘                   │ no
                 ▼                              ▼
             Product{}  ◀───── selectors ── JSON-LD? ──yes──▶ Product{} (free)
                 ▲                              │ no
                 │                              ▼
                 └──────── replay ◀── LLM synthesizes recipe ONCE ──▶ cache

Everything normalizes to one Product shape, so downstream code never knows or cares which path a record came from.

Install

pip install scrapewright               # deterministic paths (Shopify, Woo, JSON-LD)
pip install "scrapewright[llm]"        # + LLM recipe synthesis for custom HTML
pip install "scrapewright[llm,js,excel,mcp]"   # + JS rendering, XLSX, MCP server
playwright install chromium                    # only needed for --js

Use it

from scrapewright import Scrapewright

sw = Scrapewright()

# Catalog mode — a whole Shopify/WooCommerce store, deterministically
for product in sw.scrape_catalog("https://shop.example.com", max_items=200):
    print(product.brand, product.title, product.price, product.currency)

# Page mode — one custom-HTML product page.
# First call: tries JSON-LD (free); if absent, the LLM writes a recipe once.
# Every later call on that domain: replayed from the cached recipe, no LLM.
item = sw.scrape_page("https://boutique.example.com/products/wool-coat")
print(item.model_dump(exclude={"raw"}))

# Crawl mode — walk a WHOLE custom store from one listing/category URL.
# The frontier discovers product pages (deterministic, free); the first page
# pays the single synthesis cost, every other page replays the recipe.
for product in sw.crawl("https://boutique.example.com/collection", max_items=100):
    print(product.title, product.price)

CLI

Shortened. The full README is on GitHub.

Nothing above is checked by us. What we check is on the safety report.

scrapewright: common questions

Is scrapewright MCP server safe?
Yes, by our scan: it is graded A (91/100). Read the scrapewright safety report
How do I install scrapewright?
It runs remotely at scrapewright.app. Add it to Claude Code, Cursor, VS Code or Claude Desktop with the snippets above, or call it through the mcp.market gateway without installing anything.
Does scrapewright need an API key?
Yes. The registry entry asks for ANTHROPIC_API_KEY, X-API-Key.
Is scrapewright maintained?
The last commit was 21 days ago (2026-10-16). The latest release is v1.0.3.
Is scrapewright up?
100% of our last 28 checks got an answer. We check remote servers about four times a day.
What can I use instead of scrapewright?
Servers from other publishers that do the same job: Figma Context MCP server, Agent-Native Plan MCP server and Mockserver MCP server.
How does scrapewright compare with other AI and agents MCP servers?
safety score 91/100 (higher than 88% of 4,461 AI and agents servers); tools 5 (the typical AI and agents server has 6); tools that change things 0% (typical: 0%. Fewer write tools means less an agent can break). Full comparison.

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