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 duty1g · MCP Server · ★ 1.8k
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is x64dbg-mcp-server safe to install? View the security audit →
x64dbg-MCP Server MCP-powered agentic reverse engineering for x64dbg. Features • Install • Usage • Tools • Configuration • Building • <a
| Stars | 1,848 |
| Forks | 189 |
| Language | Zig |
| Category | MCP Server |
| License | MIT |
| Quality Score | 75.7967063968107/100 |
| Last Updated | 2026-09-02 |
| Created | 2026-08-22 |
| Platforms | claude-code, mcp |
| Est. Tokens | ~18k |
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x64dbg-mcp-server is x64dbg-MCP Server is a native MCP (Model Context Protocol) plugin for x64dbg that exposes the debugger's full functionality over HTTP. Connect any MCP-compatible AI assistant and control x64dbg progra. It is categorized as a MCP Server with 1.8k GitHub stars.
x64dbg-mcp-server is primarily written in Zig. It covers topics such as ai-agents, ai-debugging, binary-analysis.
You can find installation instructions and usage details in the x64dbg-mcp-server GitHub repository at github.com/duty1g/x64dbg-mcp-server. The project has 1.8k stars and 189 forks, indicating an active community.
x64dbg-mcp-server is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to x64dbg-mcp-server on Agent Skills Hub include open-reverselab, linkedin-mcp-server, Claude-Code-Everything-You-Need-to-Know. 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: