pensyve — security grade SAFE, quality 66/100

Security audit verdict: SAFE · quality 66/100

No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →

by major7apps · MCP Server · ★ 80

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

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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

agent-memoryaiai-agentsai-memoryanthropiccontext-engineeringembeddingsknowledge-graphlangchainllm

Quick Facts

Stars80
Forks11
LanguageRust
CategoryMCP Server
Quality Score65.8026394278954/100
Open Issues19
Last Updated2026-09-13
Created2026-03-18
Platformsmcp, rust
Est. Tokens~27k

pensyve alternative? Top 6 similar tools

Looking for a pensyve alternative? If you're comparing pensyve 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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  • shodh-memory by varun29ankuS · ⭐ 289

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  • omega-memory by omega-memory · ⭐ 218

    Persistent memory for AI coding agents

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Frequently Asked Questions

What is pensyve?

pensyve is Universal memory runtime for AI agents. It is categorized as a MCP Server with 80 GitHub stars.

What programming language is pensyve written in?

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

How do I install or use pensyve?

You can find installation instructions and usage details in the pensyve GitHub repository at github.com/major7apps/pensyve. The project has 80 stars and 11 forks, indicating an active community.

What are the best alternatives to pensyve?

The top alternatives to pensyve on Agent Skills Hub include vektori, Ori-Mnemos, rust-docs-mcp-server. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.

How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. 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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