IDA-PRO-MCP-multiple: 支持ida headless 多文件分析

by xxipv6 · MCP Server · ★ 52

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

Security audit verdict: CAUTION · quality 55/100

Flagged: sudo usage. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →

The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.

Quick Facts

Stars52
Forks6
LanguagePython
CategoryMCP Server
Quality Score55/100
Last Updated2026-08-23
Created2025-12-29
Platformsmcp, python
Est. Tokens~15k

About IDA-PRO-MCP-multiple

IDA MCP Server 使用说明 支持多文件、多会话并行分析。 支持平台 ✅ Windows (10/11) ✅ macOS (12+) ✅ Linux (Ubuntu 20.04+, Debian 11+) 快速开始 环境要求 安装步骤 Windows macOS Linux 配置文件（推荐） 编辑根目录 ，相对路径相对于该文件解析： toml port = 8745 # MCP 主端口 host = "127.0.0.1" # 监听地址 basesessionport = 10000 # 会话起始端口 maxsessions = 10 # 最大会话数量 fileloadtimeout = 3600 # 文件加载初始化超时（秒） analyzedir = "analyze" # 预加载的 PE/ELF/Mach-O 目录 idadir = "" # 可选，IDA...

Compatible Skills

These tools work well together with IDA-PRO-MCP-multiple for enhanced workflows:

  • openclaw-prompts-and-skills — semantic(0.35)+complementary+same_lang+similar_pop+shared_platform (62%)
  • HolyCode — semantic(0.27)+complementary+same_lang+similar_pop+shared_platform (59%)
  • DazhuangSkill-Creator — semantic(0.25)+complementary+same_lang+similar_pop+shared_platform (59%)
  • posterly — semantic(0.25)+complementary+same_lang+similar_pop+shared_platform (59%)

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How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. 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:

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