
TheCrawler
io.github.manchittlabPublished by GitHub account manchittlabv0.5.8Updated Oct 24, 2026
Universal web scraper with LLM-ready markdown, RAG chunking, PDF/DOCX support.
Overview
Local MCP server that scrapes web pages into markdown, structured data, and LLM-extracted fields, with optional contract validation and readiness diagnostics.
- What you can do
- TheCrawler crawls URLs and returns page data such as text, boilerplate-stripped markdown, links, images, metadata, JSON-LD, commerce data, forms, and detected analytics trackers. It can run LLM-powered extraction against a JSON Schema or built-in contracts like real-estate-listing and product-page, returning typed data plus validation results. A no-LLM diagnostic mode scores whether pages are ready for a contract before tokens are spent, and it also supports search-to-scrape, sitemap crawling, and PDF/DOCX parsing.
- When to use it
- Use it when an assistant needs to read public web pages, turn them into clean markdown for RAG, or pull structured fields from listings and product pages. It is also useful for checking extraction readiness before committing to a scraping workflow.
- Requirements
- Runs as a local Node.js process via the npm package or a GitHub source build; the published npm package is older than the GitHub source. LLM extraction needs a publicly reachable OpenAI-compatible chat-completions endpoint and an API key, which can be set as THECRAWLER_LLM_API_KEY. Optional SerpAPI key for reliable search. Network access required.
Installation
In SourceWeft
- Open TheCrawler in the dashboard and add it to a workspace.
- Enable the server for the chats that should use its tools.
Desktop only via STDIO. STDIO servers start a local process, so they need the SourceWeft desktop host.
Other MCP clients
Follow the launch instructions in the repository.
README
TheCrawler — AI-ready web scraper with validated extraction contracts
Scrape web pages, run LLM-powered structured extraction, or diagnose whether URLs are ready for a built-in extraction contract before spending LLM tokens. Open source engine (AGPL-3.0). $0.005 per successfully scraped page on Apify.
Start with a safe test: run one public URL with dryRun: true on Apify, or clone the current GitHub source and run the local CLI/MCP build from engine/. A small proof pack is in examples/diagnostic-challenge, including a sample readiness report at examples/diagnostic-challenge/sample-report.md.
$500 extraction readiness sprint
Use this when you need to know whether one real public-web workflow is worth automating before you spend engineering time on extraction.
- Scope: up to 25 public URLs and one target output shape.
- First step: send a public fit check through the structured issue form or use the private fit-check path on the sprint page.
- Payment: requested only after the workflow looks like a fit, by one-off $500 payment link or invoice.
- Output: a readiness report with ready, mixed, blocked, or not-worth-automating-yet guidance.
- Credit: if the workflow continues into setup or hosted usage, the $500 is credited toward that next step.
The public offer thread is GitHub issue #1. The proof pack includes a sample readiness report showing the report shape before a buyer sends URLs.
Public fit checks should use this shape:
Do not include login credentials, private URLs, personal data, or raw customer data in GitHub issues.
What makes this different
- Validated extraction contracts: select a built-in contract, get normalized data plus
validation.valid, required fields, and missing-field evidence. Current contracts:real-estate-listing,product-page,docs-page. - Brand identity extraction (
extractBrand: true): one call returns the site's ranked colorpalette,themeColor, and best-guesslogocandidates (JSON-LD / header SVG / favicons / og:image). In Playwright mode it reads rendered colors viagetComputedStyle— works on SPAs where static CSS can't. Deterministic, no LLM. - Content controls:
onlyMainContentplusincludeTags/excludeTags(CSS allow/deny) strip nav, footer, sidebars, and ads from text, markdown, links, and HTML output. Firecrawl-compatible.waitForalias supported. - HTML formats:
extractHtml(cleaned, main-content HTML) andextractRawHtml(full serialized DOM) alongside markdown. - No-LLM diagnostics: run
diagnoseModeto score source readiness, identify blockers, and save a buyer-readable Markdown report before extraction. - LLM-powered extraction: send a JSON Schema or use a contract, get parsed typed data back. Endpoint-agnostic — point at OpenAI, your own llama.cpp / vLLM / LM Studio / Ollama. You bring the LLM, no vendor lock-in.
- Adaptive crawling: Cheerio first (fast HTTP+parse), auto-fall-back to Playwright when an SPA shell is detected. Keeps browser rendering optional instead of mandatory for every page.
- Structured errors:
errorTypeenum (dns | timeout | rate-limit | blocked-bot | js-required | http-4xx | http-5xx | parse | network | unknown) +errorRetryableboolean. Agents branch programmatically — no regex on error strings. - Challenge-page detection: 200 OK responses with access-control or challenge-page bodies are flagged as
errorType: 'blocked-bot'instead of returning challenge HTML as useful content. - Out-of-box extractors: JSON-LD, microdata, commerce data (price/SKU/rating), forms with field types, 16 analytics trackers detected (GA4, GTM, Meta Pixel, Hotjar, Segment, Mixpanel, etc.), hreflang, pagination, redirect chain. Email-like and phone-like public text extraction is opt-in.
- Heading-aware RAG chunking: markdown chunked at h1-h3 boundaries with overlap and per-chunk SHA. Feed straight to a vector DB.
Three modes
Safe first run
Use dryRun: true for an Apify smoke test. The actor crawls the page but does not emit a billing event.
For the current local MCP/CLI build:
Plain crawl (default)
Returns rich PageData per URL: title, description, language, canonical URL, robots directives, full text, boilerplate-stripped markdown, links (with internal/external flag), images (with lazy-load src), meta tags, OG/Twitter Card, JSON-LD, microdata, commerce data, forms, analytics-detected, optional email-like/phone-like public text fields, social links, hreflang, pagination, redirect chain, response headers + timing, plus structured errorType + errorRetryable on failure.
LLM-powered extract mode
Crawls the URL → cleans to markdown → sends (markdown + schema) to your OpenAI-compatible chat-completions endpoint → returns parsed typed data per URL. Schema-backed extraction uses JSON Schema response format where supported, with fallbacks for endpoints that only support JSON-object or text output. Supports natural-language extractPrompt instead of/alongside the schema. The actor charges per page like normal; the LLM call cost is whatever your endpoint charges.
Note: extract mode requires a publicly-reachable LLM endpoint. LAN URLs (e.g.
http://192.168.x.x) are not reachable from Apify infrastructure. Use OpenAI, hosted vLLM, or expose your local server via a tunnel.
Set
THECRAWLER_LLM_API_KEYas an Actor environment variable so the LLM key never lands in run inputs (visible in run history).
Contract diagnostic mode
Runs crawl + readiness scoring without an LLM call. Dataset output includes per-URL verdict, readyForExtraction, score, blockers, warnings, and recommendedNextStep, plus a workflow summary. When diagnosticReport is true, the actor saves contract-diagnostic-report in the run key-value store as Markdown with a missing-readiness-signal summary. The report intentionally excludes raw extracted contact details.
Contract extract mode
Uses the selected contract schema and prompt, then appends contract validation to the extraction result. Agents can branch on validation.valid and validation.missingRequiredFields instead of trusting loose markdown. Built-in contracts currently cover real-estate-listing and product-page.
Reliability features
Search → scrape
Top-N Google results crawled in one call. Optional SerpAPI key for reliable search.
Sitemap → scrape
Sitemap.xml + sitemap-index files resolved automatically.
File extraction
PDF and DOCX URLs are auto-detected and parsed. Returns extracted text + (for PDFs) metadata, page count.
Pricing
- Crawl mode: $0.005 per page successfully scraped (failed pages don't charge).
- Extract mode / diagnostic mode: still charged per successfully scraped page. LLM endpoint cost is paid by the endpoint owner, not by this actor.
- Extraction readiness sprint: $500 after fit confirmation for one public workflow: up to 25 public URLs, one target output shape, and a ready / mixed / blocked report. Payment is by one-off link or invoice after scope is confirmed. If the workflow continues into setup or hosted usage, the $500 is credited toward that next step. If another stack is a better fit, the report says so.
Beyond the Apify Store
The current open-source engine source for this actor build is in engine/; drop it into your own Node project, MCP server, CLI, or REST API server. The published npm package is older than this GitHub source until the next npm publish, so use the GitHub-source path below for current validated-contract and MCP tools. Self-hosting avoids Apify per-page charges, while your own infrastructure and LLM endpoint costs still apply.
For Cline setup from a GitHub clone, use llms-install.md. The current GitHub source is the review path for validated contracts and MCP tools until npm is updated.
GitHub: https://github.com/manchittlab/TheCrawler · License: AGPL-3.0
Source: README.md at commit fe6019e
Tools
0Version history
1- v0.5.8LatestSep 16, 2026
Score
50% of the applicable checks met
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- Reached in the last 30 days25 pts
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- Auth declared10 pts
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- Tools listed15 pts
Answer tools/list without a credential, or ship a package that starts in a sandbox without one.
- DescriptionRequired15 pts
- Logo10 pts
- Documentation15 pts
- License10 pts