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by lazy-dinosaur · MCP Server · ★ 93
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CCXT MCP Server 한국어 버전(Korean version) CCXT MCP Server is a server that allows AI models to interact with cryptocurrency exchange APIs through the Model Context Protocol (MCP). This server uses the CCXT library to provide access to more than 100 cryptocurrency exchanges and their trading capabilities. 🚀 Quick Start Installation and Usage Global Installation Running with npx You can run it directly without installation: View help: bash npx @lazydino/
| Stars | 93 |
| Forks | 28 |
| Language | TypeScript |
| Category | MCP Server |
| License | MIT |
| Quality Score | 71.4130229778335/100 |
| Last Updated | 2026-04-23 |
| Created | 2025-03-29 |
| Platforms | claude-code, mcp, node |
| Est. Tokens | ~8k |
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ccxt-mcp is CCXT MCP Server bridges the gap between AI models and cryptocurrency trading by providing a standardized interface through the Model Context Protocol. Created to empower automated trading strategies, . It is categorized as a MCP Server with 93 GitHub stars.
ccxt-mcp is primarily written in TypeScript. It covers topics such as ai-trading, automated-trading, ccxt.
You can find installation instructions and usage details in the ccxt-mcp GitHub repository at github.com/lazy-dinosaur/ccxt-mcp. The project has 93 stars and 28 forks, indicating an active community.
ccxt-mcp is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to ccxt-mcp on Agent Skills Hub include okx-agent-trade-kit, ai-trading-agent, mcp-trader. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. It is a first-layer scan, not a manual audit — we say so rather than overstate it.
The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.
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