by huangjunsen0406 · MCP Server · ★ 3.4k
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
<a href="https://at
| Stars | 3,361 |
| Forks | 702 |
| Language | Python |
| Category | MCP Server |
| License | MIT |
| Quality Score | 44.48/100 |
| Last Updated | 2026-06-16 |
| Created | 2025-02-15 |
| Platforms | cli, mcp, python |
| Est. Tokens | ~14k |
These tools work well together with py-xiaozhi for enhanced workflows:
Looking for a py-xiaozhi alternative? If you're comparing py-xiaozhi 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.
⛓️RuleGo is a lightweight, high-performance, embedded, next-generation component orchestration rule engine fra
小智ESP32的Java企业级管理平台,提供设备监控、音色定制、角色切换和对话记录管理的前后端及服务端一体化解决方案
This open-source curriculum introduces the fundamentals of Model Context Protocol (MCP) through real-world, cr
The python library for research and development in NLP, multimodal LLMs, Agents, ML, Knowledge Graphs, and mor
Connect Cursor, Copilot & Claude AI directly to Cheat Engine via MCP. Automate reverse engineering, pointer sc
Convert documentation websites, GitHub repositories, and PDFs into Claude AI skills with automatic conflict de
Explore other popular mcp server tools:
py-xiaozhi is Open-source AI assistant ecosystem with MCP integrations, multimodal workflows, IoT support, and cross-platform voice interaction.. It is categorized as a MCP Server with 3.4k GitHub stars.
py-xiaozhi is primarily written in Python. It covers topics such as cross-platform, edge-computing, embodied-ai.
You can find installation instructions and usage details in the py-xiaozhi GitHub repository at github.com/huangjunsen0406/py-xiaozhi. The project has 3.4k stars and 702 forks, indicating an active community.
py-xiaozhi is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to py-xiaozhi on Agent Skills Hub include rulego, xiaozhi-esp32-server-java, mcp-for-beginners. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.