No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by ariadng · MCP Server · ★ 696
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is metatrader-mcp-server safe to install? View the security audit →
MetaTrader MCP Server Let AI assistants trade for you using natural language 📑 Table of Contents What is This? Features Who Is This For? Important Disclaimer Prerequisites Quick Start Trading Assistant Skill Usage Examples Available Operations WebSocket Quote Server Advanced Configuration Roadmap Development Contributing Documentation Getting Help License 🌟 What is This? MetaTrader MCP Server is a bridge that connects AI assistants (like Claude, ChatGPT) to the MetaTrader 5 trading platform. Instead of clicking buttons, you can simply te
| Stars | 696 |
| Forks | 235 |
| Language | Python |
| Category | MCP Server |
| License | MIT |
| Quality Score | 74.8852109528115/100 |
| Open Issues | 27 |
| Last Updated | 2026-03-28 |
| Created | 2025-04-10 |
| Platforms | mcp, python |
| Est. Tokens | ~132k |
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metatrader-mcp-server is Model Context Protocol (MCP) to enable AI LLMs to trade using MetaTrader platform. It is categorized as a MCP Server with 696 GitHub stars.
metatrader-mcp-server is primarily written in Python. It covers topics such as ai, finance, investment.
You can find installation instructions and usage details in the metatrader-mcp-server GitHub repository at github.com/ariadng/metatrader-mcp-server. The project has 696 stars and 235 forks, indicating an active community.
metatrader-mcp-server is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to metatrader-mcp-server on Agent Skills Hub include open-trading-api, maverick-mcp, LangAlpha. 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.
Sources & who's responsible: