shodh-memory — MCP Server by varun29ankuS

by varun29ankuS · MCP Server · ★ 246

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About shodh-memory

Shodh-Memory Persistent cognitive memory for AI agents and robots — with no LLM in the loop. Remembers what matters, forgets what doesn't, gets smarter with use. <img src="https://img.shields.io/

agent-memoryagentic-aiai-agentsai-memoryclaudecognitive-memoryedge-aigraphragknowledge-graphllm-free

Quick Facts

Stars246
Forks37
LanguageRust
CategoryMCP Server
LicenseApache-2.0
Quality Score66.9067358353955/100
Open Issues22
Last Updated2026-08-09
Created2025-12-03
Platformsclaude-code, mcp, rust
Est. Tokens~26k

shodh-memory alternative? Top 6 similar tools

Looking for a shodh-memory alternative? If you're comparing shodh-memory with other mcp server tools, these 6 projects are the closest alternatives on Agent Skills Hub — ranked by topic overlap, star count, and community traction.

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  • yantrikdb-server by yantrikos · ⭐ 171

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  • vestige by samvallad33 · ⭐ 596

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  • agentos by framersai · ⭐ 558

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Frequently Asked Questions

What is shodh-memory?

shodh-memory is Local, LLM-free memory for AI agents. A single offline Rust binary — deterministic and auditable — that learns from use, forgets the irrelevant, and strengthens what matters. No cloud, no API keys.. It is categorized as a MCP Server with 246 GitHub stars.

What programming language is shodh-memory written in?

shodh-memory is primarily written in Rust. It covers topics such as agent-memory, agentic-ai, ai-agents.

How do I install or use shodh-memory?

You can find installation instructions and usage details in the shodh-memory GitHub repository at github.com/varun29ankuS/shodh-memory. The project has 246 stars and 37 forks, indicating an active community.

What license does shodh-memory use?

shodh-memory is released under the Apache-2.0 license, making it free to use and modify according to the license terms.

What are the best alternatives to shodh-memory?

The top alternatives to shodh-memory on Agent Skills Hub include Ori-Mnemos, yantrikdb-server, omega-memory. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.

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