py-gpt: Desktop AI Assistant powered by GPT-6, GPT-5, Gemini, Claude, Grok, Ollama, DeepSeek, Perplexity, and more

by szczyglis-dev · MCP Server · ★ 2.0k

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

Security audit verdict: SAFE · quality 65/100

Flagged: installs a cron job, sudo usage. 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.

agentsaiai-assistantartificial-intelligenceautonomous-agentchatbotclaudedeepseekdesktop-appgemini

Quick Facts

Stars1,978
Forks351
LanguagePython
CategoryMCP Server
Quality Score65/100
Open Issues64
Last Updated2026-10-06
Created2023-04-09
Platformsbrowser, claude-code, gemini, mcp, python
Est. Tokens~25k

About py-gpt

PyGPT - Desktop AI Assistant Release: 2.7.12 Python: =3.10, Official website: https://pygpt.net | Documentation: https://pygpt.readthedocs.io Discord: https://pygpt.net/discord PyPi: https://pypi.org/project/pygpt-net Compiled version for Linux () and Windows 10/11 () 64-bit: https://pygpt.net/#download ❤️ Donate: https://www.buymeacoffee.com/szczyglis | https://github.com/sponsors/szczyglis-dev...

Compatible Skills

These tools work well together with py-gpt for enhanced workflows:

  • open-strawberry — semantic(0.15)+complementary+shared_fw(ollama)+rare_topics+same_lang+similar_pop+shared_platform (63%)
  • claude-code-gpt-5-codex — semantic(0.21)+complementary+rare_topics+same_lang+similar_pop+shared_platform (57%)
  • gpt-all-star — semantic(0.21)+complementary+rare_topics+same_lang+similar_pop+shared_platform (57%)
  • DemoGPT — semantic(0.17)+complementary+rare_topics+same_lang+similar_pop+shared_platform (56%)
  • ruby_llm — semantic(0.21)+complementary+shared_fw(ollama)+rare_topics+similar_pop+shared_platform (55%)

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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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