From 4f8b2ef3841a08723306163d410e276dbf94375a Mon Sep 17 00:00:00 2001
From: VS <29.varun@gmail.com>
Date: Fri, 19 Dec 2025 14:32:17 +0530
Subject: [PATCH] Add shodh-memory to Knowledge & Memory section
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Cognitive memory for AI agents with:
- Hebbian learning (associations strengthen with use)
- 3-tier architecture (working → session → long-term)
- Knowledge graphs with spreading activation
- Single ~15MB binary, runs offline on edge devices
- 688 tests, production-ready

GitHub: https://github.com/varun29ankuS/shodh-memory
---
 README.md | 1 +
 1 file changed, 1 insertion(+)

diff --git a/README.md b/README.md
index 6f861bc1..d3adfdf3 100644
--- a/README.md
+++ b/README.md
@@ -916,6 +916,7 @@ Persistent memory storage using knowledge graph structures. Enables AI models to
 - [topoteretes/cognee](https://github.com/topoteretes/cognee/tree/dev/cognee-mcp) 📇 🏠 - Memory manager for AI apps and Agents using various graph and vector stores and allowing ingestion from 30+ data sources
 - [unibaseio/membase-mcp](https://github.com/unibaseio/membase-mcp) 📇 ☁️ - Save and query your agent memory in distributed way by Membase
 - [upstash/context7](https://github.com/upstash/context7) 📇 ☁️ - Up-to-date code documentation for LLMs and AI code editors.
+- [varun29ankuS/shodh-memory](https://github.com/varun29ankuS/shodh-memory) 🦀 🏠 - Cognitive memory for AI agents with Hebbian learning, 3-tier architecture, and knowledge graphs. Single ~15MB binary, runs offline on edge devices.
 - [vectorize-io/hindsight](https://github.com/vectorize-io/hindsight) 🐍 ☁️ 🏠 - Hindsight: Agent Memory That Works Like Human Memory - Built for AI Agents to manage Long Term Memory
 - [JamesANZ/memory-mcp](https://github.com/JamesANZ/memory-mcp) 📇 🏠 - An MCP server that stores and retrieves memories from multiple LLMs using MongoDB. Provides tools for saving, retrieving, adding, and clearing conversation memories with timestamps and LLM identification.
 - [JamesANZ/cross-llm-mcp](https://github.com/JamesANZ/cross-llm-mcp) 📇 🏠 - An MCP server that enables cross-LLM communication and memory sharing, allowing different AI models to collaborate and share context across conversations.