Moonshot AI has officially brought the power of OpenClaw framework directly to the browser. The newly rebranded Kimi Claw is now native to kimi.com, providing developers and data scientists with a persistent, 24/7 AI agent environment.
This update moves the project from a local setup to a cloud-native powerhouse. This means the infrastructure for complex agents is now fully managed and ready to scale.
ClawHub: A Global Skill Registry
The core of Kimi Claw’s versatility is ClawHub. This library features over 5,000 community-contributed skills.
- Modular Architecture: Each ‘skill’ is a functional extension that allows the AI to interact with external tools.
- Instant Orchestration: Developers can discover, call, and chain these skills within the kimi.com interface.
- No-Code Integration: Instead of writing custom API wrappers, engineers can leverage existing skills to connect their agents to third-party services immediately.
40GB Cloud Storage for Data Workflows
Data scientists often face memory limits in standard chat interfaces. Kimi Claw addresses this by providing 40GB of dedicated cloud storage.
- Persistent Context: Store large datasets, technical documentation, and code repositories directly in your tab.
- RAG Ready: This space facilitates high-volume Retrieval-Augmented Generation (RAG), allowing the model to ground its responses in your specific files across sessions.
- Large-Scale File Management: The 40GB limit enables the AI to handle complex, data-heavy projects that were previously restricted to local environments.
Pro-Grade Search with Real-Time Data
To solve the knowledge cutoff problem, Kimi Claw integrates Pro-Grade Search. This feature allows the agent to fetch live, high-quality data from sources like Yahoo Finance.
- Structured Data Fetching: The AI does not just browse the web; it retrieves specific data points to inform its reasoning.
- Grounding: By pulling live financial or technical data, the agent significantly reduces hallucinations and provides up-to-the-minute accuracy for time-sensitive tasks.
‘Bring Your Own Claw’ (BYOC) & Multi-App Bridging
For devs who already have a custom setup, Kimi Claw offers a ‘Bring Your Own Claw’ (BYOC) feature.
- Hybrid Connectivity: Connect your third-party OpenClaw to kimi.com to maintain control over your local configuration while using the native cloud interface.
- Telegram Integration: You can bridge your AI setup to messaging apps like Telegram. This allows your agent to participate in group chats, execute skills, and provide automated updates outside of the browser.
- Automation Pipelines: With 24/7 uptime, these bridged agents can monitor workflows and trigger notifications autonomously.
Kimi Claw simplifies the process of building and deploying agents. By combining a massive skill library with significant storage and real-time data access, Moonshot AI is turning the browser tab into a professional-grade development environment.
Key Takeaways
- Native Cloud Integration: Kimi Claw is now officially native to kimi.com, providing a persistent, 24/7 environment that lives in your browser tab and eliminates the need for local hardware management.
- Extensive Skill Ecosystem: Developers can access ClawHub, a library of 5,000+ community skills, allowing for the instant discovery and chaining of pre-built functions into complex agentic workflows.
- High-Capacity Storage: The platform provides 40GB of cloud storage, enabling data scientists to manage large datasets and maintain deep context for RAG (Retrieval-Augmented Generation) operations.
- Live Financial Grounding: Through Pro-Grade Search, the AI can fetch real-time, high-quality data from sources like Yahoo Finance, reducing hallucinations and providing accurate market information.
- Flexible Connectivity (BYOC): The ‘Bring Your Own Claw’ feature allows engineers to connect third-party OpenClaw setups or bridge their AI agents to external platforms like Telegram group chats.
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Michal Sutter is a data science professional with a Master of Science in Data Science from the University of Padova. With a solid foundation in statistical analysis, machine learning, and data engineering, Michal excels at transforming complex datasets into actionable insights.
