ApeRAG

apecloud/ApeRAG is ranked 10,698 among these 8 peers; vercel/modelfusion is ranked 10,703.

ApeRAG ApeRAG is a production-ready RAG (Retrieval-Augmented Generation) platform that combines Graph RAG, vector search, and full-text search with advanced AI agents. Build sophisticated AI applications with hybrid retrieval, multimodal document processing, intelligent agents, and enterprise-grade management features. ApeRAG is the best choice for building your own Knowledge Graph, Context Engineering, and deploying intelligent AI agents that can autonomously search and reason across your knowledge base. Before running the following commands, make sure that Docker and

Docker Compose are installed on your machine: After running, you can access ApeRAG in your browser at: **Web Interface**: **API Documentation**: MCP (Model Context Protocol) Support ApeRAG supports MCP (Model Context Protocol) integration, allowing AI assistants to interact with your knowledge base directly. After starting the services, configure your MCP client with: **Authentication** (by priority): 1. **HTTP Authorization Header** (Recommended): 2. **Environment Variable** (Fallback): **Important**: Use your deployed API origin if not local (e. Replace with a valid API key

from your ApeRAG settings. The MCP server provides: **Collection browsing**: List and explore your knowledge collections **Hybrid search**: Search using vector, full-text, and graph methods **Intelligent querying**: Ask natural language questions about your documents Enhanced Document Parsing For enhanced document parsing capabilities, ApeRAG supports an **advanced document parsing service** powered by MinerU, which provides superior parsing for complex documents, tables, and formulas. Enhanced Document Parsing Commands Or use the Makefile shortcuts (requires GNU Make): Development & Contributing For developers interested

in source code development, advanced configurations, or contributing to ApeRAG, please refer to our Development Guide for detailed setup instructions. Advanced Index Types**: Five comprehensive index types for optimal retrieval: **Vector**, **Full-text**, **Graph**, **Summary**, and **Vision** - providing multi-dimensional document understanding and search capabilities. Intelligent AI Agents**: Built-in AI agents with MCP (Model Context Protocol) tool support that can automatically identify relevant collections, search content intelligently, and provide web search capabilities for comprehensive question answering. Enhanced Graph RAG

with Entity Normalization**: Deeply modified LightRAG implementation with advanced entity normalization (entity merging) for cleaner knowledge graphs and improved relational understanding. Multimodal Processing & Vision Support**: Complete multimodal document processing including vision capabilities for images, charts, and visual content analysis alongside traditional text processing. Hybrid Retrieval Engine**: Sophisticated retrieval system combining Graph RAG, vector search, full-text search, summary-based retrieval, and vision-based search for comprehensive document understanding. MinerU Integration**: Advanced document parsing service powered by MinerU technology, providing superior

parsing for complex documents, tables, formulas, and scientific content with optional GPU acceleration. Production-Grade Deployment**: Full Kubernetes support with Helm charts and KubeBlocks integration for simplified deployment of production-grade databases (PostgreSQL, Redis, Qdrant, Elasticsearch, Neo4j). Enterprise Management**: Built-in audit logging, LLM model management, graph visualization, comprehensive document management interface, and agent workflow management. MCP Integration**: Full support for Model Context Protocol (MCP), enabling seamless integration with AI assistants and tools for direct knowledge base access and intelligent

querying. Developer Friendly**: FastAPI backend, React frontend, async task processing with Celery, extensive testing, comprehensive development guides, and agent development