GhidraMCP: Active Socket based MCP Server for Ghidra

by 13bm · MCP Server · ★ 146

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

How to install GhidraMCP

git clone https://github.com/13bm/GhidraMCP.git

Taken from the project's README on GitHub. Check the security audit before running it.

Security audit verdict: SAFE · quality 75/100

None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. 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

Stars146
Forks22
LanguageJava
CategoryMCP Server
LicenseApache-2.0
Quality Score75/100
Open Issues2
Last Updated2026-09-22
Created2025-03-24
Platformsjava, mcp
Est. Tokens~16k

About GhidraMCP

GhidraMCP A Ghidra extension that exposes 70 reverse-engineering tools to AI assistants through the Model Context Protocol (MCP). Open a binary in Ghidra, enable the plugin, and let Claude (or any MCP client) decompile functions, rename symbols, annotate code, search for vulnerabilities, and more.

Compatible Skills

These tools work well together with GhidraMCP for enhanced workflows:

  • GhidraGPT — semantic(0.44)+complementary+same_lang+similar_pop+shared_platform (65%)
  • jadx-mcp-plugin — semantic(0.48)+shared_fw(anthropic)+same_lang+similar_pop+shared_platform (60%)
  • decyx — semantic(0.42)+complementary+shared_fw(anthropic)+similar_pop (58%)
  • GhidrAssistMCP — semantic(0.62)+same_lang+similar_pop+shared_platform (57%)
  • GhidrAssistMCP — semantic(0.61)+same_lang+similar_pop+shared_platform (56%)

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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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