Results for vectorless

Official TypeScript SDK for Vectorless — structure-preserving document retrieval without embeddings

Vectorless RAG using LLM-driven hierarchical document indexing — PDF and Markdown/Obsidian vault support

PageIndex - Vectorless RAG using LLM-based tree search

MCP server for Vectorless — give AI agents access to structure-preserving document retrieval

docSearch-skills vectorless hierarchical document search via markdown files for Claude Code and Codex

Tree-based, vectorless document RAG framework. Connect any LLM via URL/API key.

Vectorless semantic indexing SDK that converts large text into searchable knowledge trees.

Vectorless, reasoning-based RAG for document understanding. Multi-runtime (Node.js, Bun, Deno). PDF and Markdown support with OCR.

Vectorless, reasoning-based RAG — builds a hierarchical tree index from PDF, DOCX, CSV, XLSX or Markdown using any LLM. React Native compatible.

Advanced Graph-of-Thought implementation with BMSSP algorithm for vectorless document indexing and retrieval. Features selective node activation for efficient processing. Works standalone without API keys or external services. Includes backward-compatible

Vectorless, reasoning-based RAG. Builds hierarchical tree indices from PDFs and retrieves via LLM-driven tree search.

MCP server for PageIndex

MCP server for PageIndex

LLM-agnostic document indexing for js/ts - bring your own LLM and text

ragzero-core: embedding-free retrieval engine with hierarchical parsing, bottom-up semantic compression, and LLM-driven query planning.

Node-first TypeScript SDK for the PageIndex API

The Agent-Native Retrieval Engine — Hybrid Vector + Reasoning + Memory for AI Agents. HNSW indexing, tree-based reasoning retrieval, built-in RAG, MCP server, multi-agent orchestration, and agent memory architecture.