Apify Actors

Data Pipelines in Production

These are live data pipelines in production. 76 public Apify actors people already pay me to run and trust, on schedules, for agencies, data teams, and anyone feeding web data into LLMs.

illustration of a live pipeline hover a stage • click a lane to filter the catalog • click the canvas for the homepage

Perimeter and identity. Extraction starts with residential and ISP proxy pools routed with session affinity. TLS client signatures are matched to desktop browser profiles (Chrome JA3/JA4) to avoid perimeter challenge triggers before the target server delivers markup.

Execution core. Crawlee and Playwright run headless browser instances for single-page dynamic layouts, executing DOM hydration, infinite scroll pagination, and network payload interception. Static endpoints downgrade to lightweight HTTP clients to conserve compute.

Validation and delivery. Raw payloads pass through strict JSON schema validation. Records with missing keys or invalid types are rejected before storage; an in-memory Bloom filter drops duplicates. Clean items persist directly to Apify Datasets and Model Context Protocol (MCP) tool endpoints.

The swarm

Every published actor as one point, sized by active users. Click any node to open it in the catalog.

76 published actors hover a node • click to focus in list

Actor catalog

All published actors with live user counts. Click any row to expand technical details.

Run one

Every input below is the actor's own published schema, not a mockup. Edit it, copy the call, drop in your Apify token, and it runs.

input

          

Docs

Every actor runs on the Apify platform. Free account, one API token, and anything in the catalog is yours to run.

  1. 01

    Open an actor

    Pick one in the catalog and open it on Apify. Every actor page ships its full input schema and a button to run it free.

  2. 02

    Run it in the console

    Sign in, paste an input like the ones in Run one, and hit Start. Results land in a dataset you can export as JSON, CSV, or Excel.

  3. 03

    Or call it as an API

    Grab a token from Console → Settings → API, use the cURL, Python, or Node snippets above, and add a schedule to keep the data flowing.

Wire them into your agent

Every actor doubles as an MCP tool. Point your agent at mcp.apify.com, auth with your token, and it can call anything in the catalog. Append ?actors=george.the.developer/<slug> to preload a specific actor. Grab the slug from any catalog row.

Claude Code terminal
claude mcp add apify -t http https://mcp.apify.com \
  -H "Authorization: Bearer $APIFY_TOKEN"
Cursor .cursor/mcp.json
{ "mcpServers": { "apify": {
    "url": "https://mcp.apify.com",
    "headers": { "Authorization": "Bearer YOUR_TOKEN" } } } }
Codex CLI ~/.codex/config.toml
[mcp_servers.apify]
command = "npx"
args = ["-y", "mcp-remote", "https://mcp.apify.com",
        "--header", "Authorization: Bearer YOUR_TOKEN"]
Anything else ChatGPT, Windsurf, VS Code…
# any MCP-capable client, one URL:
https://mcp.apify.com?actors=george.the.developer/<slug>
# discovery tools included, agents can find actors themselves

Live numbers

Pulled from the Apify API at build time. Last refreshed .

counting runs… each bar is one actor's 30-day window • hover for detail
public actors
total users
monthly users
run success (30d)

Build one for your data