iwe — security grade SAFE, quality 68/100

Security audit verdict: SAFE · quality 68/100

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 iwe-org · MCP Server · ★ 1.7k

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

🔒 Is iwe safe to install? View the security audit →

About iwe

IWE - Memory system for you and your AI agents Turn your thinking into queryable context IWE turns a directory of markdown files into a knowledge graph — a connected structure you browse from your editor and your AI queries from the command line. Same files, same links, two interfaces. No cloud, no database, no lock-in. Version everything with git. IWE is for people who want database-style queries on their notes — "all drafts under this subtree", "every accepted decision in Q1" — without moving them into an actual database. Write in Markdown, structure with links, give AI agents the tools to navigate your knowledge. IWE it

ai-agentsai-memoryclihelixknowledge-graphknowledge-managementlanguage-serverlocal-firstlspmarkdown

Quick Facts

Stars1,654
Forks79
LanguageRust
CategoryMCP Server
LicenseApache-2.0
Quality Score67.9194794151526/100
Open Issues1
Last Updated2026-09-19
Created2024-09-20
Platformscli, mcp, rust
Est. Tokens~25k

Compatible Skills

These tools work well together with iwe for enhanced workflows:

  • fff — semantic(0.16)+complementary+rare_topics+same_lang+similar_pop+shared_platform (60%)
  • soulforge — semantic(0.23)+complementary+rare_topics+similar_pop+shared_platform (57%)
  • Empryo — semantic(0.23)+complementary+rare_topics+similar_pop+shared_platform (57%)
  • WakeGPT — semantic(0.18)+complementary+same_lang+similar_pop+shared_platform (56%)

iwe alternative? Top 6 similar tools

Looking for a iwe alternative? If you're comparing iwe 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.

  • pi-llm-wiki by zosmaai · ⭐ 581

    Self-maintaining, Obsidian-compatible knowledge base for pi — turn raw sources into an interlinked wiki that c

  • okf-skills by scaccogatto · ⭐ 359

    The OKF toolkit for Claude Code — author, maintain, validate & visualize Open Knowledge Format bundles. Plugin

  • obsidian-second-brain by eugeniughelbur · ⭐ 4.6k

    Persistent memory for Claude Code and 6 other CLI agents, stored as plain markdown in your Obsidian vault. Sto

  • basic-memory by basicmachines-co · ⭐ 4.0k

    AI conversations that actually remember. Never re-explain your project to your AI again. Join our Discord: htt

  • swarmvault by swarmclawai · ⭐ 649

    The local-first LLM Wiki: open-source knowledge graph builder, RAG knowledge base, and agent memory store. Bui

  • vestige by samvallad33 · ⭐ 628

    Cognitive Deterministic Memory Security OS for Agentic AI. Deterministic root-cause retrieval that reaches bac

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Frequently Asked Questions

What is iwe?

iwe is Markdown knowledge graph — LSP for your editor, CLI + MCP memory for your AI agents. It is categorized as a MCP Server with 1.7k GitHub stars.

What programming language is iwe written in?

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

How do I install or use iwe?

You can find installation instructions and usage details in the iwe GitHub repository at github.com/iwe-org/iwe. The project has 1.7k stars and 79 forks, indicating an active community.

What license does iwe use?

iwe 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 iwe?

The top alternatives to iwe on Agent Skills Hub include pi-llm-wiki, okf-skills, obsidian-second-brain. 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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