Zleap-AI/SAG

Health v2 · maintenance only

Adoption not part of the score

2425 stars · 150 forks observed · 2026-08-28

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

SAG is an open-source retrieval architecture and knowledge base application that replaces both traditional RAG and GraphRAG with event-entity indexing and query-time dynamic hyperedges. It ships as a Python package (zleap-sag), a desktop app, and a CLI that mounts a Knowledge MCP server into agents like Codex and Claude Code.

Use cases

• build a searchable, source-traceable knowledge base from scattered documents
• answer multi-hop questions with better recall than RAG or GraphRAG
• connect a knowledge base to coding agents via MCP
• migrate and back up knowledge bases across instances
• extract entities and relations from documents into a knowledge graph
• give agents shared context with citations

When to choose

• you need semantic retrieval plus relational reasoning in one system
• you want a self-hosted knowledge base with traceable, cited answers
• you want to plug a knowledge base into LLM agents through MCP
• you are benchmarking retrieval on multi-hop QA datasets

When to avoid

• you need a battle-tested, widely-adopted enterprise RAG stack
• you only need simple keyword or plain vector search without graph reasoning
• you require non-Python/non-Node runtimes or managed cloud deployment
• you need long-term stability guarantees from a mature project

Facets

application · maturity active

rag search-engine vector-database agent-framework mcp nlp machine-learning artificial-intelligence large-language-models databases python cross-platform self-hosted cli graphrag knowledge-graph event-entity-indexing multi-hop-qa retrieval-architecture mcp-server desktop-app cli-tool pypi-package knowledge-base retrieval-augmented-generation ai-agents search data-engineering natural-language-processing nodejs desktop

Member repositories

For agents

markdown · JSON · MCP: product_card(name="Zleap-AI/SAG")