openloomi: Open-source AI coworker

by melandlabs · MCP Server · ★ 1.0k

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

How to install openloomi

git clone https://github.com/melandlabs/openloomi.git

Taken from the project's README on GitHub. Check the security audit before running it.

Security audit verdict: SAFE · quality 66/100

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. Full audit →

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.

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Quick Facts

Stars1,032
Forks47
LanguageTypeScript
CategoryMCP Server
LicenseApache-2.0
Quality Score66/100
Open Issues20
Last Updated2026-09-24
Created2026-04-10
Platformsmcp, node
Est. Tokens~15k

About openloomi

An AI That Always Remembers You. English | 简体中文 What is OpenLoomi? OpenLoomi is an open-source AI workspace that runs on your desktop. It connects to the tools you already use — messaging apps, email, calendar, documents, project trackers — and builds a Holistic Context Graph of your people, projects, and decisions. Features What it does

Compatible Skills

These tools work well together with openloomi for enhanced workflows:

  • first-tree — semantic(0.22)+complementary+same_lang+similar_pop+shared_platform (53%)
  • AgentHub — semantic(0.19)+complementary+same_lang+similar_pop+shared_platform (52%)

openloomi alternative? Top 6 similar tools

Looking for a openloomi alternative? If you're comparing openloomi 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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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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