scrapedatshi-mcp

# scrapedatshi-mcp MCP (Model Context Protocol) server for the [scrapedatshi](https://scrapedatshi.com) RAG pipeline API. Use scrapedatshi's scraping, crawling, extraction, and vector DB sync tools directly from **Claude Desktop** — no code required. --- ## What you can do Just talk to Claude naturally: - *"Scrape https://docs.example.com and give me the chunks"* - *"Extract the text from this PDF: https://example.com/annual-report.pdf"* - *"Extract all tables from this local PDF: C:/Users/me/Documents/financials.pdf"* - *"Chunk this PDF URL: https://my-bucket.s3.amazonaws.com/report.pdf"* — PDF URLs are automatically detected and extracted - *"Crawl https://example.com/products and extract the title and price from every page"* - *"Sync https://docs.example.com to my Pinecone index using OpenAI embeddings"* - *"Crawl the entire docs.stripe.com site (all 800 pages) and inject it into my Pinecone index"* — large sites are auto-batched server-side, no manual pagination needed - *"What embedding providers does scrapedatshi support?"* - *"Inspect my Pinecone index and tell me what embedding model was used"* - *"Query my Pinecone index for information about API authentication"* - *"Query my LanceDB with hybrid search — I need to find exact IDs and names, not just semantic matches"* - *"Chunk https://docs.example.com using hierarchical chunking so the LLM gets full context on retrieval"* - *"Ingest all the JSON files in my ./scrapy_output/ folder into my Pinecone index"* --- ## Tools exposed | Tool | What it does | |---|---| | `verify_provider_key` | Verify an LLM or embedding API key + get live model list | | `get_usage_guide` | Returns the guided wizard flow and tool selection reference | | `scrape_url` | Scrape a URL and return clean Markdown — no chunking, just the raw text | | `pdf_extract` | Extract text or tables from a PDF (URL or local file) — no chunking, no embedding needed | | `chunk_url` | Scrape & chunk a single URL into RAG-ready text segments | | …