pensyve: Universal memory runtime for AI agents

by major7apps · MCP Server · ★ 95

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

How to install pensyve

pip install pensyve          # Python (PyPI)
npm install @pensyve/sdk     # TypeScript (npm)

Taken from the project's README on GitHub.

Security audit verdict: SAFE · quality 65/100

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-memoryaiai-agentsai-memoryanthropiccontext-engineeringembeddingsknowledge-graphlangchainllm

Quick Facts

Stars95
Forks16
LanguageRust
CategoryMCP Server
Quality Score65/100
Open Issues4
Last Updated2026-10-04
Created2026-03-18
Platformsmcp, rust
Est. Tokens~27k

About pensyve

Pensyve Universal memory runtime for AI agents. Framework-agnostic, protocol-native, offline-first. Without memory With Pensyve Your agent stops being amnesiac. Decisions, patterns, and outcomes persist across sessions — and the right context surfaces when it's needed. Why Pensyve How Pensyve solves it

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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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