# Wayback Machine Extractor - Archive.org Downloader (`caulleonard/wayback-extractor`) Actor Recover dead or deleted websites. Download HTML, files, and snapshot metadata from the Wayback Machine. - **URL**: https://apify.com/caulleonard/wayback-extractor.md - **Developed by:** [Fatih Şahinbaş](https://apify.com/caulleonard) (community) - **Categories:** Developer tools, SEO tools - **Stats:** 2 total users, 1 monthly users, 0.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $0.50 / 1,000 results This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. 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. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md). If your project is in a different language, use 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 ## Wayback Machine Downloader — Recover Deleted Websites & Archive.org Data **Download Wayback Machine snapshots, recover dead websites, and scrape archive.org history — HTML, files, and metadata — in one run.** This Wayback Machine downloader queries the official `web.archive.org` CDX API to list every archived capture of a domain, then optionally saves the raw historical HTML and files so you can restore, migrate, or analyze sites that no longer exist online. Whether a site was shut down, a page was deleted, or you need the historical version of a competitor's store, this actor turns the Internet Archive into structured, downloadable data. ### What this actor does - 🔎 **List every archived snapshot** of any URL or full domain from the Wayback Machine (archive.org). - 📄 **Download historical HTML** exactly as it was captured, with the Wayback banner stripped (raw `id_` captures). - 🗂️ **Extract archived files** — PDFs, images, and other assets — using MIME filters. - 🕒 **Filter by date range** to grab a specific point in a website's history. - 💾 **Structured output** — clean JSON metadata to the dataset, raw content to the Key-Value Store. ### Use cases - **Dead website recovery** — the site is gone, but archive.org still has it. Pull the last working snapshot and rebuild. - **Deleted page retrieval** — recover a single removed URL and its historical content. - **Content migration** — export an old site's pages before decommissioning a legacy platform. - **Competitor & market research** — inspect how a competitor's website, pricing, or messaging looked in past years. - **Digital archiving & compliance** — capture a verifiable historical record of any public web page. - **SEO & link recovery** — find old URLs and content that used to rank. ### Input | Field | Type | Description | |---|---|---| | `targetUrl` | string | Site or page to recover, e.g. `example.com`. **Required.** | | `mode` | select | `single_page`, `full_site` (domain crawl), `files_only`, or `snapshot_list` (metadata only). | | `fromDate` | string | Start date `YYYYMMDD` (optional). | | `toDate` | string | End date `YYYYMMDD` (optional). | | `mimeFilter` | array | Keep only matching MIME types, e.g. `application/pdf`, `image/`. | | `only200` | boolean | Skip non-200 captures (redirects, errors). Default `true`. | | `limit` | integer | Max snapshots to process. `0` = no limit. | | `saveContent` | boolean | `false` = metadata only (cheaper). `true` = download HTML/files to Key-Value Store. | #### Example input ```json { "targetUrl": "example.com", "mode": "full_site", "fromDate": "20100101", "toDate": "20151231", "only200": true, "limit": 500, "saveContent": true } ```` ### Output Each snapshot is pushed to the dataset as a clean JSON record: ```json { "timestamp": "20100603215612", "original_url": "http://www.example.com/", "mimetype": "text/html", "statuscode": "200", "digest": "AB2CD3EF4GH5IJ6KL7MN8OP9QR0ST1UV", "captured_at": "2010-06-03T21:56:12", "raw_url": "https://web.archive.org/web/20100603215612id_/http://www.example.com/" } ``` When `saveContent` is enabled, the raw historical HTML and files are stored in the run's **Key-Value Store**, keyed by timestamp and URL, ready to download or re-host. ### How it works The actor uses the Internet Archive's **CDX Server API** to enumerate captures, deduplicating identical content by digest. For downloads it requests the raw `id_` capture URL, which returns the original archived bytes without the Wayback Machine's injected toolbar, JavaScript, or CSS — so the recovered HTML is clean and usable. No login, no API key, no proxy required. Data comes straight from the public Internet Archive. ### Tips - Start with `mode: snapshot_list` and a small `limit` to preview what the archive holds before downloading. - Large domains return thousands of captures — use `fromDate`/`toDate` and `limit` to stay focused and control cost. - Use `mimeFilter: ["application/pdf"]` to recover only archived documents. ### Pricing Pay-per-event: you pay a small fee per run start, per snapshot listed, and per file downloaded. Run metadata-only (`saveContent: false`) for the cheapest previews; enable downloads only when you need the content. *** *This actor reads publicly available data from the Internet Archive (archive.org). Respect the copyright and terms of use of any recovered content.* # Actor input Schema ## `targetUrl` (type: `string`): Site or page to recover, e.g. example.com ## `mode` (type: `string`): What to extract ## `fromDate` (type: `string`): YYYYMMDD, optional ## `toDate` (type: `string`): YYYYMMDD, optional ## `mimeFilter` (type: `array`): e.g. application/pdf, image/ ## `only200` (type: `boolean`): Skip non-200 captures (redirects, errors) ## `limit` (type: `integer`): Safety cap. 0 = no limit ## `saveContent` (type: `boolean`): Off = only metadata to Dataset (cheaper). On = HTML/files stored. ## Actor input object example ```json { "targetUrl": "geocities.com", "mode": "snapshot_list", "mimeFilter": [], "only200": true, "limit": 500, "saveContent": false } ``` # 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 '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "targetUrl": "geocities.com" }; // Run the Actor and wait for it to finish const run = await client.actor("caulleonard/wayback-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 '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "targetUrl": "geocities.com" } # Run the Actor and wait for it to finish run = client.actor("caulleonard/wayback-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 '{ "targetUrl": "geocities.com" }' | apify call caulleonard/wayback-extractor --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=caulleonard/wayback-extractor", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Wayback Machine Extractor - Archive.org Downloader", "description": "Recover dead or deleted websites. Download HTML, files, and snapshot metadata from the Wayback Machine.", "version": "0.1", "x-build-id": "WhhaqlKp7cIy0aW9G" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/caulleonard~wayback-extractor/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-caulleonard-wayback-extractor", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/caulleonard~wayback-extractor/runs": { "post": { "operationId": "runs-sync-caulleonard-wayback-extractor", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/caulleonard~wayback-extractor/run-sync": { "post": { "operationId": "run-sync-caulleonard-wayback-extractor", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "required": [ "targetUrl", "mode" ], "properties": { "targetUrl": { "title": "Target URL / Domain", "type": "string", "description": "Site or page to recover, e.g. example.com" }, "mode": { "title": "Extract Mode", "enum": [ "single_page", "full_site", "files_only", "snapshot_list" ], "type": "string", "description": "What to extract", "default": "snapshot_list" }, "fromDate": { "title": "From date", "type": "string", "description": "YYYYMMDD, optional" }, "toDate": { "title": "To date", "type": "string", "description": "YYYYMMDD, optional" }, "mimeFilter": { "title": "MIME filter", "type": "array", "description": "e.g. application/pdf, image/", "default": [], "items": { "type": "string" } }, "only200": { "title": "Only HTTP 200", "type": "boolean", "description": "Skip non-200 captures (redirects, errors)", "default": true }, "limit": { "title": "Max snapshots", "type": "integer", "description": "Safety cap. 0 = no limit", "default": 500 }, "saveContent": { "title": "Download content to Key-Value Store", "type": "boolean", "description": "Off = only metadata to Dataset (cheaper). On = HTML/files stored.", "default": false } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```