# Table Extractor — Scrape HTML Tables from Any URL to JSON/CSV (`eliai/webpage-tables-extractor`) Actor

Table extractor for webpages: pass a URL and get every HTML table back as structured rows — JSON via the API or dataset, CSV via one-click export. For analysts, developers, and AI agents that need tabular data without writing a parser. Pay only for results, no code required.

- **URL**: https://apify.com/eliai/webpage-tables-extractor.md
- **Developed by:** [Anthony Snider](https://apify.com/eliai) (community)
- **Categories:** Developer tools, Automation
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

$20.00 / 1,000 table extractions

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.

Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event

## What's an Apify Actor?

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.
Actors are written with capital "A".

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.
The best way to integrate Actors is as follows.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — the [REST API](https://docs.apify.com/api/v2.md).

For usage examples, see the [API](#api) section below.

For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).

# README

## Webpage Tables Extractor

Turn any webpage's HTML `<table>`s into clean, structured JSON — headers and rows ready for a spreadsheet, an LLM, or a data pipeline.

Live on the Apify Store — run it instantly or call it as an agent tool via Apify MCP.

### What you get

- Every real data `<table>` on the page, parsed to JSON.
- Each table: `index`, `headers`, `rowCount`, and `rows` (objects keyed by header, falling back to column index).
- Layout/spacer tables (single column or fewer than 2 rows) are automatically skipped.
- Loose `colspan` handling so cells stay aligned with headers.
- Single URL or bulk URLs in one run.

### Input

```json
{
  "url": "https://en.wikipedia.org/wiki/List_of_largest_companies_by_revenue",
  "maxUrls": 25
}
```

Or bulk:

```json
{
  "urls": [
    "https://example.com/report-a",
    "https://example.com/report-b"
  ]
}
```

### Output

One dataset item per page:

```json
{
  "url": "https://en.wikipedia.org/wiki/List_of_largest_companies_by_revenue",
  "tableCount": 1,
  "tables": [
    {
      "index": 0,
      "headers": ["Rank", "Name", "Industry", "Revenue (USD millions)"],
      "rowCount": 50,
      "rows": [
        {
          "Rank": "1",
          "Name": "Walmart",
          "Industry": "Retail",
          "Revenue (USD millions)": "648,125"
        }
      ]
    }
  ]
}
```

Pricing: pay-per-event — charged once per page processed.

# Actor input Schema

## `url` (type: `string`):

A single webpage URL to extract HTML tables from.

## `urls` (type: `array`):

Multiple webpage URLs to extract tables from. Combined with the single URL above.

## `maxUrls` (type: `integer`):

Maximum number of URLs to process in one run.

## Actor input object example

```json
{
  "url": "https://en.wikipedia.org/wiki/List_of_largest_companies_by_revenue",
  "maxUrls": 25
}
```

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "url": "https://en.wikipedia.org/wiki/List_of_largest_companies_by_revenue"
};

// Run the Actor and wait for it to finish
const run = await client.actor("eliai/webpage-tables-extractor").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = { "url": "https://en.wikipedia.org/wiki/List_of_largest_companies_by_revenue" }

# Run the Actor and wait for it to finish
run = client.actor("eliai/webpage-tables-extractor").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"])
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "url": "https://en.wikipedia.org/wiki/List_of_largest_companies_by_revenue"
}' |
apify call eliai/webpage-tables-extractor --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "command": "npx",
            "args": [
                "mcp-remote",
                "https://mcp.apify.com/?tools=eliai/webpage-tables-extractor",
                "--header",
                "Authorization: Bearer <YOUR_API_TOKEN>"
            ]
        }
    }
}

```

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/a4BWt3rq1SSGfdly6/builds/U815O15KnMXq2I8A3/openapi.json