mcpField
A
Apify

Apify

Remote
pipeworx.ioBrowser Automation1Updated 6d ago

About Apify

Apify is an MCP server for web data collection, letting users run Apify Actors, scrape pages, and retrieve dataset results. It combines configurable Actor runs with a page-scraping wrapper and tools for existing datasets.

Key features

  1. 01Run Apify Actors and retrieve results
  2. 02Scrape pages into Markdown
  3. 03Fetch items from existing datasets

Use cases

  1. 01Run a web-scraping or automation Actor
  2. 02Prepare page content as RAG-friendly Markdown
  3. 03Read data produced by an earlier Actor run

MCP support

It exposes tools to MCP clients for running Actors, scraping pages, and fetching dataset items. It runs through the Pipeworx gateway or as a local stdio MCP server and requires the user's Apify API key.

Configuration

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

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

Apify MCP — run web-scraping Actors and fetch their dataset results.

Part of Pipeworx — an MCP gateway connecting AI agents to 1872+ live data sources. This is an independent, unofficial integration — not affiliated with, endorsed by, or published by the upstream provider.

Tools

ToolDescription
apify_run_actorRun an Apify Actor (a cloud scraping/automation program) and get its dataset results in a single blocking call. The run is capped at 300 seconds. Pass the Actor input as an input object — its shape depends on the Actor. Example: apify_run_actor({ actorId: "apify~web-scraper", input: { startUrls: [{ url: "https://example.com" }] }, _apiKey: "your-token" }). Browse Actors at https://apify.com/store.
apify_scrape_urlScrape a single web page (or crawl from it) and get clean, RAG-friendly markdown content. Convenience wrapper around the "apify~website-content-crawler" Actor. Example: apify_scrape_url({ url: "https://docs.apify.com/api/v2", _apiKey: "your-token" }).
apify_dataset_itemsFetch items from an existing Apify dataset (e.g. the output of a prior Actor run). Example: apify_dataset_items({ datasetId: "abc123", limit: 50, _apiKey: "your-token" }).

Quick Start

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

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

tools/list at https://gateway.pipeworx.io/apify/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 1872+ 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/apify_run_actor. 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": {
    "apify": {
      "command": "npx",
      "args": ["-y", "@pipeworx/mcp-apify"]
    }
  }
}

Or run it directly to confirm it starts:

npx -y @pipeworx/mcp-apify

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 Apify 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.