Upload files to process and index them for searchable knowledge retrieval using RAG (Retrieval-Augmented Generation) technology.
MIT
133,413 tools. Last updated 2026-05-25 13:06
"Tools for Automatically Indexing Code Files and RAG (Retrieval-Augmented Generation)" matching MCP tools:
- Ask questions about memory files using retrieval-augmented generation to get answers from stored content with configurable search modes.MIT
- Create a named local vector index for retrieval-augmented generation. Documents added are embedded via Ollama for local RAG without cloud dependencies.
- Stores a knowledge fragment with source and evidence tier metadata for future retrieval via semantic RAG queries.MIT
- Defines the project directory for indexing, enabling code search and analysis.MIT
- Retrieve the indexing status of your codebase—state, statistics, and progress. Use this to check if indexing is complete and your project context is ready.Elastic 2.0
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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
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- Read and analyze code files with advanced filtering and chunking, automatically ignoring common artifact directories and files for efficient code examination.MIT
- Index files, directories, YouTube videos, or GitHub repositories into PinRAG's searchable database for retrieval-augmented generation with automatic format detection and batch processing.MIT
- Inspect a URL's indexing and crawl status in Bing Webmaster Tools. Returns HTTP status, indexing state, crawl date, page title, link counts, and blockage info.MIT
- Creates or updates a node in a persistent graph memory for long-term RAG retrieval. Requires initialized NFT matrix; if missing, purchase license key first.Business Source 1.1
- Parse code files into semantic chunks such as functions, classes, and methods to improve retrieval in RAG systems.
- Execute RAG queries against Amazon Bedrock Knowledge Bases to retrieve relevant documents using vector search for enhanced information retrieval.MIT
- Search uploaded documents using RAG to find answers with citations. Ask questions to retrieve information from your knowledge base.MIT
- Perform semantic search and question-answering on your Obsidian vault using a local retrieval-augmented generation pipeline.MIT
- Retrieve a complete list of all files stored in the RAG system for document management and semantic search operations.MIT
- Delete files from the RAG system to manage storage and maintain relevant content for retrieval-augmented generation tasks.MIT
- Generate Stylus/Rust smart contract code for Arbitrum using RAG context and version-aware generation. Supports ERC standards and custom contracts with optional tests.MIT
- Add files to a RAG system for document retrieval, supporting PDF, DOCX, TXT, MD, CSV, and JSON formats to enable semantic search and information access.MIT
- Initialize indexing for a project by scanning source files to build a searchable index of code identifiers, methods, types, and signatures.MIT
- Add text content to a knowledge base for RAG indexing, making it searchable and retrievable through AI applications.MIT