Industry FirstVisual Multimodal Agent Workstation
No complex setup — start your agent workflow with one click
Pre-built capabilities and visual workstation — use as soon as installed
Full-chain observability and auditability — every call under your control
Say goodbye to SSH logins and tedious environment setup. We understand the high barrier of OpenClaw operations — GateClaw encapsulates underlying logic into intuitive UI operations, instantly activating your dedicated Agent and making automation tools truly accessible.
Comprehensive protection for your API Keys and wallet private keys. Through our proprietary sandbox isolation environment, all agents operate only within authorized scope. Assets remain under your full control with system-level permission lockdown, achieving zero-risk interaction.
No more unpredictable fees. Our transparent model combines fixed subscriptions with daily credit limits. Clearly foresee monthly expenses with real-time circuit breaker mechanisms, ensuring every resource is spent wisely.
Following professional exchange listing audit standards, we carefully curate the official Skills library. Through multi-dimensional security audits, we physically isolate any malicious code scripts, protecting user environments at the source.
Sensitive credentials are securely hosted and never exposed to tools or models. Secure injection, access whitelisting, and leakage detection ensure every call remains safe and under control.
No blind upstream updates — avoid unpredictable compatibility and security vulnerabilities. Independent version locking technology ensures agents always run on the most stable foundation.
New features are built entirely on Hooks and plugin architecture, physically isolated from the core engine. Feature iterations don't interfere with each other — even a single plugin failure won't affect your core assets and business.
Frequently asked questions about GateClaw, AI Agent and Web3 automation
GateClaw is an AI-powered Web3 agent workstation developed by Gate. It allows users to deploy AI agents for crypto trading, market analysis, and blockchain automation through a visual interface. GateClaw integrates Gate MCP skills, exchange APIs, and on-chain data, enabling AI agents to safely interact with trading infrastructure, wallets, and blockchain networks.
AI agents deployed through GateClaw can perform a wide range of Web3 automation tasks, including analyzing crypto market data, executing automated trading strategies, monitoring on-chain transactions and smart money flows, managing portfolio operations, and generating market intelligence reports. By combining AI models with Gate MCP skills, agents can automate workflows that previously required manual trading or scripting.
Gate MCP (Model Context Protocol) is a protocol that allows AI agents to interact with external tools and crypto infrastructure. Through Gate MCP, AI agents can securely access market data APIs, trading execution engines, blockchain data, and wallet interactions. GateClaw provides the execution environment where these MCP skills can run safely and efficiently.
Yes. GateClaw is designed with exchange-grade security standards to protect user assets and execution environments. Key security mechanisms include encrypted API key management, sandbox isolation for agent execution, strict permission control for wallet and trading access, and security audits for plugins and skills. These protections ensure AI agents operate only within authorized scopes.
No. GateClaw provides a visual interface that allows users to deploy AI agents without complex infrastructure setup. Instead of managing servers or writing scripts, users can launch automation workflows through a graphical environment that integrates OpenClaw strategies, MCP skills, and trading infrastructure. Developers can still extend functionality through APIs and custom skills if needed.
Traditional trading bots follow predefined rules or simple algorithms. GateClaw enables AI-powered agents that can analyze complex market signals, adapt strategies dynamically, combine multiple data sources, and interact with Web3 infrastructure through MCP skills. This allows AI agents to perform more intelligent automation compared to rule-based trading bots.