Ontos-AI/knowhere

Health v2 · maintenance only

Flags: young

Adoption not part of the score

2673 stars · 292 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

Knowhere is a document ingestion and parsing platform that transforms unstructured documents (PDF, DOCX, XLSX, PPTX, images) into structured, RAG-ready chunks with preserved hierarchy, tables, and metadata. It is offered as a managed REST API (Chunking-as-a-Service), an open-source self-hosted stack, and an MCP server for AI agents like Cursor, Claude Code, and Codex.

Use cases

• parse resumes from pdfs into structured chunks
• prepare messy PDFs for RAG pipelines
• extract tables and layouts from documents for LLMs
• chunk long technical documents with hierarchy preserved
• give AI agents document parsing via MCP
• build agentic RAG over unstructured documents
• convert docx and pptx files into clean JSON chunks

When to choose

• you need high-quality, structure-preserving chunking for RAG or agents
• you want an MCP server so coding agents can parse and search documents
• you deal with complex PDFs with tables, merged cells, or hundreds of pages
• you want a managed API instead of maintaining your own parsing pipeline

When to avoid

• you only need simple plain-text extraction from clean documents
• you need fully offline processing and cannot use a cloud API or self-host
• your documents are already well-structured markdown or JSON
• you need formats not yet supported like epub or html

Facets

service · maturity active

parser rag etl pdf ocr mcp sdk search-engine artificial-intelligence pdf developer-tools apis python self-hosted cli chunking-as-a-service document-parsing agentic-rag document-intelligence vectorless-rag hierarchical-chunking mcp-server rest-api retrieval-augmented-generation ai-agents natural-language-processing nodejs docker web-server

Member repositories

For agents

markdown · JSON · MCP: product_card(name="Ontos-AI/knowhere")