mcpField
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Hyperbrowser

Hyperbrowser

Remote
pipeworx.ioBrowser Automation0Updated 2d ago

About Hyperbrowser

Hyperbrowser connects its AI-agent browsing API to MCP for agents that scrape, extract, and crawl web pages. It handles JavaScript-rendered pages and can use an LLM with a prompt or JSON schema to produce structured data.

Key features

  1. 01Scrape page content, HTML, links, and metadata
  2. 02Extract structured JSON from web pages
  3. 03Crawl a site from a starting URL
  4. 04Handle JavaScript-rendered pages

Use cases

  1. 01Extract product names and prices from pages
  2. 02Collect multi-page site content for further processing

MCP support

Exposes web scraping, structured extraction, and site crawling tools to MCP clients through the Pipeworx gateway or as a local stdio server.

Configuration

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

Endpointhttps://gateway.pipeworx.io/hyperbrowser/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-hyperbrowser

Hyperbrowser MCP — wraps the Hyperbrowser AI-agent browsing API (hyperbrowser.ai). Scrape, extract, and crawl web pages from headless cloud browsers built for AI agents.

Part of Pipeworx — an MCP gateway connecting AI agents to 1881+ live data sources. This is an independent, unofficial integration — not affiliated with, endorsed by, or published by the upstream provider.

Tools

ToolDescription
hyperbrowser_scrapeScrape a single web page from a cloud browser and return clean content (markdown, html, links, and page metadata). Handles JS-rendered pages. Example: hyperbrowser_scrape({ url: "https://example.com", _apiKey: "your-key" })
hyperbrowser_extractExtract structured JSON data from one or more web pages using an LLM. Provide a JSON schema and/or a natural-language prompt describing what to pull. Example: hyperbrowser_extract({ urls: ["https://example.com"], prompt: "Get the product name and price", schema: { type: "object", properties: { name: { type: "string" }, price: { type: "string" } } }, _apiKey: "your-key" })
hyperbrowser_crawlCrawl a website starting from a URL, following links and scraping each page to markdown. Use maxPages to bound the crawl. Example: hyperbrowser_crawl({ url: "https://example.com", maxPages: 10, _apiKey: "your-key" })

Quick Start

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

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

tools/list at https://gateway.pipeworx.io/hyperbrowser/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 1881+ 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/hyperbrowser_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": {
    "hyperbrowser": {
      "command": "npx",
      "args": ["-y", "@pipeworx/mcp-hyperbrowser"]
    }
  }
}

Or run it directly to confirm it starts:

npx -y @pipeworx/mcp-hyperbrowser

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 Hyperbrowser data" })

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

More

License

MIT

Comments

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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.