Download entire documentation websites for offline RAG indexing by providing a URL, enabling configurable depth and asset capture.
MIT
650,501 tools. Updated 2026-10-13 20:50
"Hybrid RAG System for Indexing DevOps eBooks and Online Documentation" matching MCP tools:
- Index a dataset so text chunks become searchable. Splits content into RAG-ready chunks and generates embeddings for semantic retrieval.MIT
- 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
- Keep RAG search current by re-indexing catalog schema after changes. Uses schema hashing to skip unchanged schemas.Apache 2.0
- Check the current status of the RAG documentation index, including total chunks, configured sources, and last update times.Apache 2.0
- Register a GitHub repository as a documentation source for RAG indexing. Specify repo, branch, and file patterns, then run ingestion to make the docs searchable.Apache 2.0
Matching MCP Servers
- AlicenseNot gradedqualityCmaintenanceEnables AI agents to use a hybrid dense+sparse RAG system with tag-based long-term memory (importance, knowledge-type decay, access-frequency boost) via MCP tools for document ingestion, hybrid search, staged reranking, forgetting, and index management.MIT
- AlicenseAqualityCmaintenanceAn MCP server that provides a search_docs tool with hybrid retrieval (BM25 + dense vectors) and cross-encoder reranking, backed by evaluation, prompt-injection guardrails, and OpenTelemetry tracing.1MIT
Matching MCP Connectors
PDFCheck Online provides hosted PDF metadata tools over MCP. Inspect author fields, dates, page counts, PDF versions and creator/producer software when available. Anonymous access plus authenticated history/usage workflows. Metadata is editable; software indicators do not prove authenticity or AI authorship. Setup and limits: https://pdfcheck.online/ai-agents. Hindi website: https://pdfcheck.online/hi.
MCP server for Vonage API documentation, code snippets, tutorials, and troubleshooting.
- Get precise answers to any question about Lamatic.ai documentation by searching all indexed docs with RAG.MIT
- List jobs with filters by status, date range, department, or search. Returns paginated results for career-site sync, reporting, and external system indexing.MIT
- Search the RAG corpus with semantic and keyword hybrid search to find relevant content marketing ideas.MIT
- Find answers in MailKite documentation with natural-language queries, returning the most relevant sections via hybrid vector and keyword search.MIT
- Extract clean, tag-free plain text from any webpage for RAG embedding and vector indexing. Returns title, word count, and token metrics.MIT
- Search project documentation and README files using semantic search to answer conceptual questions about how features work or system architecture.MIT
- List all Foundry VTT worlds connected to the relay, providing online status, system, and version details.MIT
- Displays session efficiency: token usage, RAG savings, and learned patterns. Call after multi-step tasks to reveal context saved by RAG versus full documentation loads.MIT
- Display session efficiency statistics: token usage, RAG savings, and patterns learned. Quantify context saved by RAG versus loading full documentation.MIT
- Perform hybrid web searches combining broad coverage with technical documentation focus. Choose between general web search or documentation-optimized mode to get relevant results with titles, URLs, and snippets.MIT
- Retrieve top-k passages from a sample RAG corpus using various retrieval methods to see what context a RAG system would surface for a query.MIT
- Remove outdated or incorrect documentation sources by URL to clean up your RAG system and improve search accuracy.MIT
- Check the MCP connection status, active mode (online/offline/hybrid), and current project info for EasyEDA Pro.MIT
- Scan local RAG source documents to detect prompt injection, secrets, and PII before indexing.MIT
- Look up how to use any CrewAI feature, tool, or pattern by querying the internal documentation RAG engine. Returns relevant snippets with source URIs.MIT