Scrape a public URL to create a searchable knowledge base. Extracts content from web pages (including JavaScript-rendered), chunks it, and indexes for RAG.
MIT
781,599 tools. Updated 2026-11-14 11:00
"A server/tool for RAG-based documentation scraping and retrieval with SSE support" matching MCP tools:
- Ask Bright Data's support assistant Sophie about products, APIs, MCP usage, zones, scraping, account setup, or product selection; continue threads with dialog_id.MIT
- Create a searchable knowledge base from plain text, automatically chunked and indexed for RAG retrieval. Ideal for FAQs, product specs, and policies.MIT
- Searches Apify and Crawlee documentation by full-text query, letting you choose the Apify, Crawlee JavaScript, or Crawlee Python source to find relevant pages and snippets.MIT
- Ask natural-language questions and receive grounded, cited answers from Calypso's knowledge base, with support for file IDs and multi-turn follow-ups.MIT
- Create a named document collection to group related evidence bundles for cross-document semantic search and RAG-based Q&A.MIT
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Matching MCP Connectors
Web scraping for AI agents. Extract text and metadata from any URL worldwide. $0.005/page.
SSE Accept hint
- Find relevant Redis documentation and knowledge base articles by asking questions about concepts, data structures, features, and common use cases like caching, rate limiting, and RAG.MIT
- Perform semantic search over a stored memory namespace to retrieve the most relevant entries. Use this to recall context for RAG pipelines.MIT
- Upload a local document into the Proofpane governance RAG corpus for governed retrieval: the cloud parses, DLP-scrubs, chunks, embeds, and audits it so contents are searchable by collection.MIT
- Check the current status of the RAG documentation index, including total chunks, configured sources, and last update times.Apache 2.0
- Search Python library documentation using natural language queries to find specific functions, classes, and usage examples from consolidated sources.MIT
- Get precise answers to any question about Lamatic.ai documentation by searching all indexed docs with RAG.MIT
- Search Haystack Enterprise Platform documentation for components, pipelines, and AI features, filtering by section to retrieve relevant excerpts with source URLs.Apache 2.0
- Retrieve comprehensive documentation and code examples for any library by providing its name and a specific topic. Automatically fetches relevant sections, ensuring up-to-date information for accurate coding.MIT
- Find document types semantically similar to a query via multilingual semantic search. Matches by meaning, not exact text, using RAG-based embeddings.MIT
- Retrieve support metadata for SPSS methods, including command family, support tier, coverage assertions, and documentation tags.MIT
- Extract clean content from a public URL, returning Markdown, text, metadata, links, JSON-LD schema, and sections for scraping, RAG ingestion, or content analysis.MIT
- Create a searchable knowledge tool for retrieving documents. Integrates selected knowledge folders into a custom tool for RAG-based document search.MIT
- Add knowledge entries to a RAG system to store insights, tips, and best practices. Categorize and tag them for efficient retrieval.MIT
- Execute a complete RAG workflow: generate query embeddings, search document chunks, and return a direct answer grounded only in the retrieved context.MIT
- Submit an async scraping task for any URL. Returns a task ID to poll progress and retrieve data later. Handles JS-heavy, rate-limited, or long-running pages.MIT