awesome-openclaw-zh and awesome-claws

The two tools are **complements**, as one provides practical, Chinese-language use cases and deployment guides for OpenClaw, while the other curates a broader list of AI agents inspired by the OpenClaw concept.

awesome-openclaw-zh
50
Established
awesome-claws
48
Emerging
Maintenance 13/25
Adoption 10/25
Maturity 11/25
Community 16/25
Maintenance 10/25
Adoption 10/25
Maturity 11/25
Community 17/25
Stars: 165
Forks: 22
Downloads:
Commits (30d): 0
Language:
License: MIT
Stars: 324
Forks: 36
Downloads:
Commits (30d): 0
Language:
License: MIT
No Package No Dependents
No Package No Dependents

About awesome-openclaw-zh

cogine-ai/awesome-openclaw-zh

OpenClaw 中文实战库:176 个可复制使用场景,从部署到5分钟上手到完全精通。案例覆盖自动化、内容创作、运营增长与安全使用。

Provides platform-agnostic deployment guides (macOS, Windows, Linux VPS, multi-agent setups) and native integrations with Chinese communication platforms (Feishu, DingTalk, WeChat Work) through standardized channel adapters. Organizes 184 production workflows across 14 categories—from RAG-based knowledge systems and multi-agent teams to social monitoring and security automation—each with executable code and configuration templates rather than abstract examples.

About awesome-claws

machinae/awesome-claws

A curated list of awesome AI agents inspired by OpenClaw

Covers 34+ open-source AI agent implementations across TypeScript, Python, Rust, Go, and other languages, ranging from ultra-lightweight binaries (4MB, ESP32) to feature-rich multi-agent platforms. Projects span specialized domains—mobile automation, edge hardware, research workflows, privacy-first deployments—with common patterns including multi-channel messaging, sandboxed execution, MCP tool integration, and persistent memory. The collection emphasizes production-ready alternatives to the original OpenClaw architecture across different resource constraints and deployment environments.

Scores updated daily from GitHub, PyPI, and npm data. How scores work