LibreAI / Agents IA / ghidra-mcp
// agents · bethington/ghidra-mcp

ghidra-mcp

ghidra-mcp est un projet de agents IA open source, créé par bethington (bethington/ghidra-mcp sur GitHub). Il compte 4 877 étoiles sur GitHub et 229 forks, il est publié sous la licence Apache-2.0 et a été mis à jour pour la dernière fois sur GitHub le 8 octobre 2026.

Ghidra MCP server with 200+ tools that let AI assistants drive real reverse-engineering work

★ 4,9 k étoiles⑂ 229 forksApache-2.0mis à jour oct. 2026
▦ visuel — le README de ce projet ne contient aucune capture intégrable,
voici donc un emplacement réservé. Le guide ci-dessous est complet malgré tout.
// détails du projet

Détails du projet

Étoiles GitHub
4 877
Forks
229
Licence
Apache-2.0
Dernière mise à jour sur GitHub
8 octobre 2026
Catégorie
Agents IA
Type de fiche
Guide d'installation complet
// fonctionnement

Comment ça marche

  1. Clarify your target

    Decide whether you will analyze binaries in the Ghidra GUI or run the headless server for automated/CI analysis.

  2. Install prerequisites

    Install Ghidra, Java 21, and Python 3.10+ (Maven 3.9+ or the bundled Gradle wrapper for builds).

  3. Build and deploy the extension

    Clone the repo and use the setup tool to run preflight, install prerequisites, build, and deploy into your Ghidra installation.

  4. Connect your MCP client and analyze

    Start Ghidra (or the headless server), connect your AI client to the bridge, and run a first function-documentation workflow.

// fonctionnalités

Pourquoi on l'adore

209 MCP tools

A comprehensive API surface covering decompilation, call graphs, cross-references, memory inspection, and more.

Full write access

Rename, retype, comment, and create structures — with convention enforcement (auto-fix, warn, or reject) keeping names and types consistent.

Dynamic analysis

P-code emulation to run functions in isolation, plus live debugger integration with breakpoints, stepping, registers, and memory reads.

Cross-binary documentation transfer

SHA-256 function-hash matching propagates documentation across binary versions automatically.

Batch operations

Bulk renaming, commenting, and typing with far fewer API calls, plus atomic transactions and configurable timeouts.

GUI, headless, and server modes

Run inside the Ghidra GUI, headless for Docker/CI pipelines, and against shared Ghidra Servers with version-control workflows.

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// lancez-le

Lancez-le vous-même

  1. Clone the repository

    Clone the project and enter its directory.

    git clone https://github.com/bethington/ghidra-mcp.git
    cd ghidra-mcp
  2. Preflight and build

    Run the setup tool's preflight against your Ghidra install, install prerequisites, and build (adjust the Ghidra path to your machine).

    python -m tools.setup preflight --ghidra-path ~/ghidra_12.1.4_PUBLIC
    python -m tools.setup ensure-prereqs --ghidra-path ~/ghidra_12.1.4_PUBLIC
    python -m tools.setup build
  3. Deploy to Ghidra

    Deploy the extension; it installs into Ghidra, starts it, and runs MCP health checks.

    python -m tools.setup deploy --ghidra-path ~/ghidra_12.1.4_PUBLIC
// cas d'usage

Ce que vous pouvez créer

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// faq

Questions fréquentes

Who maintains ghidra-mcp?

Developer bethington, who describes it as built by a reverse engineer for daily use on real binaries; it is community-maintained and distinct from the NSA's Ghidra project itself.

Is ghidra-mcp free?

Yes — the server is Apache-2.0 licensed, and Ghidra itself is free and open source. You supply your own AI client/model access.

Does it need a paid API key?

The server itself needs no key, but the AI client you connect (for example a commercial coding assistant) may require its own subscription or API key.

How does it compare to other Ghidra MCP servers?

The README positions it as the most comprehensive option — 209 tools with write access, emulation, debugging, and Ghidra Server support, versus the handful of mostly read-only tools in simpler bridges.

How do I get started?

Install Ghidra 12.1.4, Java 21, and Python 3.10+, clone the repo, and run the `python -m tools.setup` preflight, build, and deploy sequence from the README.

// continuez l'exploration

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// plus en agents

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