shodh-memory: Local, LLM-free memory for AI agents

by varun29ankuS · MCP Server · ★ 300

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

How to install shodh-memory

claude mcp add shodh-memory -- npx -y @shodh/memory-mcp
npx @shodh/memory-mcp setup-hooks

Taken from the project's README on GitHub.

Security audit verdict: SAFE · quality 67/100

None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours.

The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.

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

Quick Facts

Stars300
Forks41
LanguageRust
CategoryMCP Server
LicenseApache-2.0
Quality Score67/100
Open Issues26
Last Updated2026-10-05
Created2025-12-03
Platformsclaude-code, mcp, rust
Est. Tokens~26k

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/

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How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. It is a first-layer scan, not a manual audit — we say so rather than overstate it.

The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.

Sources & who's responsible:

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