Ask questions enhanced by RAG context from xAI Collections, with cached responses for fast repeat queries.
MIT
260,585 tools. Last updated 2026-07-05 07:35
"Information or uses related to a rag" matching MCP tools:
- Ask natural-language questions about your browsing history and get AI-powered answers using RAG. Filter results by event type, domain, or time window.MIT
- Retrieve detailed information about a specific RAG project within the Calibre ebook library, including its configuration, contents, and organization for semantic search and contextual conversations.
- Export a completed dataset as text in jsonl, csv, json, md, xml, or rag format for LLM fine-tuning, spreadsheet analysis, or structured interchange.MIT
- Retrieve detailed information about any Apify Actor, including description, input schema, pricing, stats, and README, using its ID or full name.MIT
- Clear cached RAG retrievals to force fresh results from source when context changes.MIT
Matching MCP Servers
- Alicense-qualityAmaintenanceEnables AI agents to query OpenRouter model information including prices, ELO rankings, context, and perform comparisons.Last updated221MIT
- Flicense-qualityBmaintenanceEnables any MCP-compatible AI assistant to search, filter, and retrieve information from a local document collection using a hybrid search pipeline with vector, BM25, reranking, and LLM enrichment.Last updated4
Matching MCP Connectors
Transform any blog post or article URL into ready-to-post social media content for Twitter/X threads, LinkedIn posts, Instagram captions, Facebook posts, and email newsletters. Pay-per-event: $0.07 for all 5 platforms, $0.03 for single platform.
Turn any shopping list into a ready-to-checkout grocery cart across 26 European supermarkets.
- Execute a complete retrieval-augmented generation workflow to answer user questions using document context, automatically handling embedding, semantic search, and strict context-grounded responses.MIT
- Create relationships between existing memory entities by specifying a subject, verb, and object to connect related information.MIT
- Generate vector embeddings from text for semantic search, RAG, clustering, or similarity tasks. Choose between query or document input type and adjust model quality and dimensionality.MIT
- Find coins related to a given coin by category or sector similarity. Provide the canonical coin ID to retrieve a list of related coins, optionally limiting the number.MIT
- Retrieve a list of all knowledge folders in your organization, each containing documents for RAG capabilities.MIT
- Query Vectara's RAG system to retrieve search results and generate contextual responses using specified corpus keys and API parameters for accurate information extraction.Apache 2.0
- Lists all available RAG categories indexed by RAGMap to help you identify suitable retrieval servers for your task.MIT
- Update a memory's content, title, or location with optimistic concurrency to prevent overwrites. Optionally move it to a new path or update related paths.MIT
- Find threat signatures related to a specific signature using pattern similarity. Requires Pro tier or Novyx Cloud.MIT
- Create a searchable knowledge tool for retrieving documents. Integrates selected knowledge folders into a custom tool for RAG-based document search.MIT
- Retrieve LAZY-RAG cache statistics including hits, misses, hit rate, and cache size to monitor caching performance.MIT
- Parse code files into semantic chunks such as functions, classes, and methods to improve retrieval in RAG systems.MIT
- Retrieves related product cards from a Shop.app product page. Provide a product ID and optional limit to get up to 50 related items.MIT
- Retrieve all known information about a topic, including linked memories, related entities, and a timeline.MIT