by szczyglis-dev · MCP Server · ★ 1.7k
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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 Overview PyGPT is all-in-one Desktop AI Assistant that provides direct interaction with OpenAI language models, including , , , and more, through the . By utilizing other SDKs and , the application also supports alternative LLMs, like those available on , locally available models via (like , ,, or ), and other models like , , , and . This assistant offers multiple modes of operation such as chat, assistants, agents, completions, and image-related tasks like image generation and image analysis. PyGPT has filesystem capabilities for file I/O, can generate and run Python code, execute system commands, execute custom commands and manage file transfers. It also allows models to perform web searches with the
| Stars | 1,666 |
| Forks | 317 |
| Language | Python |
| Category | MCP Server |
| Quality Score | 35.8/100 |
| Open Issues | 45 |
| Last Updated | 2026-02-06 |
| Created | 2023-04-09 |
| Platforms | browser, claude-code, gemini, mcp, python |
| Est. Tokens | ~4269k |
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py-gpt is Desktop AI Assistant powered by GPT-5, GPT-4, o1, o3, Gemini, Claude, Ollama, DeepSeek, Perplexity, Grok, Bielik, chat, vision, voice, RAG, image and video generation, agents, tools, MCP, plugins, spe. It is categorized as a MCP Server with 1.7k GitHub stars.
py-gpt is primarily written in Python. It covers topics such as ai, ai-assistant, artificial-intelligence.
You can find installation instructions and usage details in the py-gpt GitHub repository at github.com/szczyglis-dev/py-gpt. The project has 1.7k stars and 317 forks, indicating an active community.
The top alternatives to py-gpt on Agent Skills Hub include ruby_llm, Awesome-AITools, ax. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.