awesome-selfhosted-ai: Curated list of self-hosted open-source AI: local LLMs, chat UIs, agents, MCP servers, RAG, speech and image

by glincker · MCP Server · ★ 85

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

Security audit verdict: SAFE · quality 56/100

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.

ai-agentsawesomeawesome-listhomelabllmlocal-ailocal-llmmcp-serverollamaopen-source

Quick Facts

Stars85
Forks9
LanguageJavaScript
CategoryMCP Server
LicenseCC0-1.0
Quality Score56/100
Last Updated2026-11-02
Created2026-10-31
Platformsmcp, node
Est. Tokens~25k

About awesome-selfhosted-ai

Awesome Self-Hosted AI Open-source AI you can run on your own hardware or server. 303 projects across local LLMs, chat interfaces, agents, MCP servers, RAG, speech and image generation. A weekly job checks every project against the GitHub API, and anything archived, deleted or silent for over a year moves to UNMAINTAINED.md.

Compatible Skills

These tools work well together with awesome-selfhosted-ai for enhanced workflows:

  • awesome-jev — semantic(0.20)+complementary+same_lang+similar_pop+shared_platform (57%)

awesome-selfhosted-ai alternative? Top 6 similar tools

Looking for a awesome-selfhosted-ai alternative? If you're comparing awesome-selfhosted-ai 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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    Self-hosted AI workspace with agents, skills, and tools (Gmail, Calendar) that runs entirely on your own provi

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    The whole local AI stack in one executable: it runs and manages local AI models across every GPU, and it's a s

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  • captain-claw by kstevica · ⭐ 193

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    [archived] c4 GenAI Suite

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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:

View on GitHub → Browse MCP Server tools