apecloud/ApeRAG

Health v2 · maintenance only

Adoption not part of the score

1322 stars · 147 forks observed · 2026-10-07

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

ApeRAG is a production-ready RAG platform combining Graph RAG, vector search, and full-text search with AI agents and MCP support. It offers multimodal document indexing, knowledge graph construction, and scalable Kubernetes deployment.

Use cases

• build a knowledge graph from my documents
• self-host a RAG platform with hybrid search
• expose my knowledge base to AI assistants via MCP
• chat with my documents using graph and vector retrieval
• deploy a production RAG service on Kubernetes
• parse and index multimodal documents for AI search

When to choose

• you need GraphRAG with knowledge graph construction out of the box
• you want hybrid retrieval combining vector, full-text, and graph search
• you need MCP integration so AI assistants can query your knowledge base
• you want a self-hosted, Kubernetes-scalable RAG platform

When to avoid

• you only need a lightweight embedding library to embed in your own app
• you want a fully managed cloud RAG service with zero ops
• your hardware cannot meet the 2-core/4GB minimum requirements

Facets

service · maturity active

rag search-engine vector-database agent-framework mcp chatbot nlp llm-inference large-language-models self-hosted python self-hosted cloud graphrag knowledge-graph hybrid-search multimodal context-engineering mcp-server production-ready retrieval-augmented-generation ai-agents search natural-language-processing docker kubernetes web-server

Member repositories

For agents

markdown · JSON · MCP: product_card(name="apecloud/ApeRAG")