Show HN: Embenx – agentic memory layer for AI agents
Category: ai-ml
Tags: ai-agents, vector-search, retrieval-augmented-generation, model-context-protocol, synthetic-data
Score: 7.0/10 (Innovation: 7, Technical: 7, Documentation: 8, Utility: 6)
Embenx is a Python library that provides a unified retrieval and memory layer for AI agents, combining vector search, synthetic data generation, and a Model Context Protocol (MCP) server. It's interesting because it packages advanced research concepts like temporal/spatial memory and quantization into a practical toolkit, bridging the gap between simple vector indices and full vector databases.
Target audience: ai engineers, ml researchers, backend devs building agentic systems
Repository: https://github.com/adityak74/embenx · Python · MIT · 2 stars
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