yifanfeng97/Hyper-Extract

Health v2 · maintenance only

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Adoption not part of the score

3376 stars · 398 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

Hyper-Extract is a Python CLI tool that transforms unstructured documents into structured knowledge using LLMs, producing graphs, hypergraphs, and spatio-temporal extractions with a single command. It supports multiple LLM providers (OpenAI, Anthropic, DeepSeek), exports to formats like Obsidian vaults, and includes an MCP server for querying knowledge abstracts from AI agents.

Use cases

• extract knowledge graphs from unstructured documents
• build a hypergraph from text with an LLM
• convert PDFs and notes into structured knowledge
• query extracted knowledge from Claude Desktop via MCP
• export a knowledge graph to an Obsidian vault
• build RAG-ready knowledge bases from documents

When to choose

• you want one-command extraction of structured knowledge from messy text
• you need hypergraph or spatio-temporal extraction beyond plain knowledge graphs
• you want LLM-provider flexibility including Claude and DeepSeek
• you want to feed extracted knowledge into AI agents via MCP

When to avoid

• you need a fully managed GUI-based knowledge graph platform
• you want deterministic extraction without LLM costs or API dependencies
• you need a non-Python or embedded environment

Facets

cli-tool · maturity active

nlp rag cli llm-inference mcp search-engine large-language-models developer-tools python cli cross-platform knowledge-graph hypergraph information-extraction obsidian-export unstructured-text natural-language-processing knowledge-graphs retrieval-augmented-generation

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