# Mintlify Docs Scraper โ€” Docs to Clean Markdown (`straightforward_hydra/mintlify-docs-scraper`) Actor Extract any Mintlify / llms.txt documentation site as clean Markdown: one row per page with title, section, summary & content. For RAG & LLMs. No key. - **URL**: https://apify.com/straightforward\_hydra/mintlify-docs-scraper.md - **Developed by:** [Dev D](https://apify.com/straightforward_hydra) (community) - **Categories:** Automation, Developer tools, Other - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $5.00 / 1,000 doc pages 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. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js/docs.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python/docs.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/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 ## Mintlify Docs Scraper โ€” Docs to Clean Markdown ๐Ÿ“„ **Point it at any Mintlify (or `llms.txt`-enabled) documentation site and get the whole thing as clean Markdown โ€” one structured row per page: title, section, summary, content and word count. No API key, no HTML scraping, no anti-bot.** Mintlify-hosted docs (used by thousands of dev-tool companies) automatically publish machine-readable endpoints: - **`/llms.txt`** โ€” an index of every documentation page (title, `.md` URL, summary). - **`.md`** โ€” each page rendered as clean Markdown. This Actor reads that index and pulls every page, giving you ready-to-use docs content. The same `llms.txt` standard is served by a growing list of docs platforms, so this works beyond Mintlify too. --- ### What you get per page `title` ยท `section` ยท `summary` ยท `markdown` (clean page content) ยท `word_count` ยท `page_url` ยท `path` ยท `site` ยท `source`. ### Examples **Whole docs site as Markdown** ```json { "docsUrl": "https://resend.com/docs" } ```` **Fast index only (no content, cheap)** ```json { "docsUrl": "https://resend.com/docs", "includeContent": false } ``` **First 50 pages** ```json { "docsUrl": "https://docs.example.com", "maxPages": 50 } ``` ### Use cases - **RAG & "chat with your docs"** โ€” ingest a whole docs site into a vector DB in clean Markdown. - **AI coding assistants & agents** โ€” feed up-to-date product docs as context. - **Docs migration & backup** โ€” export a Mintlify site to portable Markdown. - **Competitive & content analysis** โ€” diff, search or audit documentation at scale. ### Notes - **No API key.** Uses the site's public `llms.txt` index and per-page `.md` endpoints. - **`docsUrl` = the docs base**, e.g. `https://resend.com/docs` or `https://docs.example.com`. The Actor looks for `llms.txt` there. - **Works on Mintlify sites and any site that publishes `llms.txt`.** If a site has no `llms.txt`, the run stops with a clear message. - **`includeContent: false`** returns just the page list (title, url, section, summary) โ€” fast and cheap when you only need the map. - Content belongs to each documentation site's owner and is subject to their terms โ€” use responsibly. *** #### Keywords Mintlify, llms.txt, documentation scraper, docs to markdown, docs extractor, RAG, LLM context, vector database, developer docs, API docs, markdown export, docs migration, AI docs, chat with docs, no API key. # Actor input Schema ## `docsUrl` (type: `string`): Base URL of the documentation site, e.g. "https://resend.com/docs" or "https://docs.example.com". The Actor reads its llms.txt index. ## `includeContent` (type: `boolean`): If on, fetch each page's full Markdown content. Turn off for a fast, cheap index-only list (title, url, section, summary). ## `maxPages` (type: `integer`): Cap on the number of documentation pages to return. ## Actor input object example ```json { "docsUrl": "https://resend.com/docs", "includeContent": true, "maxPages": 1000 } ``` # 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 = { "docsUrl": "https://resend.com/docs" }; // Run the Actor and wait for it to finish const run = await client.actor("straightforward_hydra/mintlify-docs-scraper").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`๐Ÿ’พ 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); }); // ๐Ÿ“š Want to learn more ๐Ÿ“–? Go to โ†’ 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 = { "docsUrl": "https://resend.com/docs" } # Run the Actor and wait for it to finish run = client.actor("straightforward_hydra/mintlify-docs-scraper").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("๐Ÿ’พ Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # ๐Ÿ“š Want to learn more ๐Ÿ“–? Go to โ†’ https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "docsUrl": "https://resend.com/docs" }' | apify call straightforward_hydra/mintlify-docs-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=straightforward_hydra/mintlify-docs-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Mintlify Docs Scraper โ€” Docs to Clean Markdown", "description": "Extract any Mintlify / llms.txt documentation site as clean Markdown: one row per page with title, section, summary & content. For RAG & LLMs. No key.", "version": "0.1", "x-build-id": "I5RFaWAESpyQyhhG9" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/straightforward_hydra~mintlify-docs-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-straightforward_hydra-mintlify-docs-scraper", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/straightforward_hydra~mintlify-docs-scraper/runs": { "post": { "operationId": "runs-sync-straightforward_hydra-mintlify-docs-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/straightforward_hydra~mintlify-docs-scraper/run-sync": { "post": { "operationId": "run-sync-straightforward_hydra-mintlify-docs-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "docsUrl" ], "properties": { "docsUrl": { "title": "Docs site URL", "type": "string", "description": "Base URL of the documentation site, e.g. \"https://resend.com/docs\" or \"https://docs.example.com\". The Actor reads its llms.txt index." }, "includeContent": { "title": "Fetch page Markdown", "type": "boolean", "description": "If on, fetch each page's full Markdown content. Turn off for a fast, cheap index-only list (title, url, section, summary).", "default": true }, "maxPages": { "title": "Max pages", "minimum": 1, "maximum": 10000, "type": "integer", "description": "Cap on the number of documentation pages to return.", "default": 1000 } } }, "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 } } } } } } } } } } ```