mcpField
S
Scrapingant

Scrapingant

Remote
pipeworx.ioBrowser Automation0Updated 5w ago

About Scrapingant

Scrapingant is an MCP server for clients that need to retrieve and process web pages through the ScrapingAnt API. It supports rendered scraping, clean Markdown output, and structured extraction.

Key features

  1. 01Fetch raw HTML from web pages
  2. 02Render JavaScript-heavy pages
  3. 03Return clean Markdown
  4. 04Extract structured page data

Use cases

  1. 01Collect HTML from a web page
  2. 02Prepare article text for an LLM
  3. 03Extract product fields from a page

MCP support

Exposes ScrapingAnt scraping, Markdown conversion, and extraction tools to MCP clients. It can run as a local stdio server or through the Pipeworx gateway.

Configuration

Remote servers need no local install. Pick your client, then copy the config or install in one click.

Endpointhttps://gateway.pipeworx.io/scrapingant/mcp
Copy install command
Claude CodeTerminal
Cursor.cursor/mcp.json
VS Code.vscode/mcp.json
Claude Desktopclaude_desktop_config.json
Windsurf~/.codeium/windsurf/mcp_config.json

Run commands in a terminal; paste JSON into the client’s MCP config and restart. Servers that need sign-in will prompt on first connect.

Tools

Details

From the project README

mcp-scrapingant

ScrapingAnt MCP — wraps the ScrapingAnt web scraping API (scrapingant.com)

Part of Pipeworx — an MCP gateway connecting AI agents to 1683+ live data sources.

Tools

ToolDescription
scrapingant_scrapeScrape a web page and return its raw HTML via ScrapingAnt (headless-browser rendering + rotating proxies). Handles JS-heavy sites and anti-bot pages. Example: scrapingant_scrape({ url: "https://example.com", browser: true, _apiKey: "your-key" })
scrapingant_markdownFetch a web page and return clean, LLM-ready Markdown (boilerplate stripped) via ScrapingAnt. Ideal for feeding page content to a model. Example: scrapingant_markdown({ url: "https://example.com/article", _apiKey: "your-key" })
scrapingant_extractExtract structured data from a web page using ScrapingAnt AI extraction. Describe the fields you want in extract_properties (comma-separated) and get back a JSON object with matching camelCase keys. Example: scrapingant_extract({ url: "https://example.com/product", extract_properties: "product title, price(number), full description", _apiKey: "your-key" })

Quick Start

Add to your MCP client (Claude Desktop, Cursor, Windsurf, etc.):

{
  "mcpServers": {
    "scrapingant": {
      "url": "https://gateway.pipeworx.io/scrapingant/mcp"
    }
  }
}
What this endpoint actually serves

tools/list at https://gateway.pipeworx.io/scrapingant/mcp returns the tools in the table above plus the shared Pipeworx meta-tools — ask_pipeworx, discover_tools, search_within, remember/recall and the rest of the gateway-wide set. So the tool count you see is larger than this table: a single-pack endpoint currently lists roughly 30 shared tools alongside the pack's own. The connection's initialize response states its exact scope, and is the authoritative answer for a given day.

This is deliberate, not multiplexing by accident. The meta-tools are what let a scoped connection answer a question this pack does not cover — via ask_pipeworx, which routes across the whole catalog — without you adding a second MCP server. There is currently no way to mount a pack endpoint without them; if the extra schemas cost you more context than the routing is worth, connect to the full gateway once rather than to several pack endpoints.

Or connect to the full Pipeworx gateway to get every pack's tools listed directly, instead of just this one's:

{
  "mcpServers": {
    "pipeworx": {
      "url": "https://gateway.pipeworx.io/mcp"
    }
  }
}

Both URLs reach the same gateway and the same 1683+ data sources. The only difference is which pack's tools are listed directly; ask_pipeworx reaches all of them from either one.

No MCP client? Call it over HTTP

This pack takes your own API key (_apiKey) — we don't front one for it, so there's no curl here that would run without it. Inspect any tool: GET https://gateway.pipeworx.io/v1/tools/scrapingant_scrape. Find one: POST https://gateway.pipeworx.io/v1/tools/search_packs with {"query":"..."}.

Standalone (no gateway account)

This package also runs as a local stdio MCP server — no Pipeworx account, no gateway round-trip:

{
  "mcpServers": {
    "scrapingant": {
      "command": "npx",
      "args": ["-y", "@pipeworx/mcp-scrapingant"]
    }
  }
}

Or run it directly to confirm it starts:

npx -y @pipeworx/mcp-scrapingant

It speaks MCP over stdin/stdout and answers initialize/tools/list/tools/call for only this pack's tools — none of the shared meta-tools the gateway connection above adds. Same source, same tools, no ask_pipeworx routing.

Using with ask_pipeworx

Instead of calling tools directly, you can ask questions in plain English — this works on the pack endpoint above as well as on the full gateway:

ask_pipeworx({ question: "your question about Scrapingant data" })

The gateway picks the right tool and fills the arguments automatically.

More

License

MIT

Comments

Markdown supported

New to MCP?

From what the protocol is to installing your first server, these answers cover most first questions.

An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.