Upload files to process and index them for searchable knowledge retrieval using RAG (Retrieval-Augmented Generation) technology.
MIT
127,390 tools. Last updated 2026-05-05 15:50
"Information about RAG (Retrieval-Augmented Generation) or rag-related topics" matching MCP tools:
- Ask questions about memory files using retrieval-augmented generation to get answers from stored content with configurable search modes.MIT
- Search uploaded documents using RAG to find answers with citations. Ask questions to retrieve information from your knowledge base.MIT
- Delete files from the RAG system to manage storage and maintain relevant content for retrieval-augmented generation tasks.MIT
- Create a named local vector index for retrieval-augmented generation. Documents added are embedded via Ollama for local RAG without cloud dependencies.
- Execute a complete RAG workflow in a single step to answer user questions: generate embeddings, perform semantic search, and answer using only retrieved context.
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- Alicense-qualityCmaintenanceEnhances AI model capabilities with structured, retrieval-augmented thinking processes that enable dynamic thought chains, parallel exploration paths, and recursive refinement cycles for improved reasoning.Last updated23MIT
- AlicenseAqualityCmaintenanceProvides local Retrieval-Augmented Generation (RAG) capabilities using Ollama for embeddings and ChromaDB for vector storage. It enables users to ingest and perform semantic searches across PDF, Markdown, and TXT documents within MCP-compatible clients.Last updated4201MIT
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- Search the web for current information, news, articles, and websites to find up-to-date content, research topics, or answer questions about recent events.Apache 2.0
- Stores a knowledge fragment with source and evidence tier metadata for future retrieval via semantic RAG queries.MIT
- Retrieve details about a specific code generation session using its session ID to access browser automation results and generated test code.MIT
- Retrieve recent decisions from Clawket's RAG repository to review decisions made in previous sessions. Filter by project plan or creation timestamp. Returns a list sorted by newest first. Use for session context updates.
- Search project artifacts such as design decisions, specs, and documents using hybrid semantic and keyword search. Retrieve relevant snippets with similarity scores to quickly find previous decisions or documentation on specific topics.
- Convert web pages to clean markdown format by extracting content, removing unnecessary elements, and ranking information for RAG applications.MIT
- Create a knowledge base in Amazon Bedrock to store and organize documents for retrieval-augmented generation (RAG), supporting vector search, custom parsing, and chunking strategies.MIT
- Search the web for current information using DuckDuckGo, returning summaries, related topics, and source URLs. No API key required. Privacy-first.
- Extract answers from web pages by analyzing content with AI. Provide a URL and question to get specific information from the page.MIT
- Perform web searches to retrieve structured, source-cited data optimized for AI agents and RAG applications.MIT
- Retrieve AI-synthesized answers and curated web results with extracted content and relevance scores. Filter by domain or recency. Built for LLM and agent RAG pipelines.
- Search the web for current information, news, articles, and websites to answer questions about recent events, research topics, or find specific resources.Apache 2.0
- Ask questions with RAG-enhanced context from xAI Collections; a lazy cache speeds up repeated queries by up to 100,000x.
- Retrieve complete details of a CRS report by report number, including summary, authors, topics, related legislation, and downloadable formats.MIT