Ghidra MCP Server

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A production-ready Model Context Protocol (MCP) server that bridges Ghidra's powerful reverse engineering capabilities with modern AI tools and automation frameworks. 219 MCP tools, battle-tested AI workflows, and the most comprehensive Ghidra-MCP integration available — now including P-code emulation, live debugger integration, and PCode-graph data flow analysis.

Quickstart: install a release (no clone, no build)

Every release ships the two pieces you need: the Ghidra extension (GhidraMCP-<version>.zip) and the MCP bridge (ghidra_mcp_bridge-<version>-py3-none-any.whl).

1. Install the prerequisites: Ghidra 12.1.4, Java 21 and uv. The extension only loads in the exact Ghidra version it was built for.
2. Install the extension: in Ghidra's project window, File > Install Extensions, click +, pick the GhidraMCP-<version>.zip you downloaded, and restart Ghidra.
3. Enable the plugin: in the project window, File > Configure > Utility > Configure, tick GhidraMCPPlugin. Check it answers:

bash curl http://127.0.0.1:8089/check_connection # {"status": "ok", "server_kind": "gui", "version": "7.0.0"}

4. Install the bridge (copy the wheel's link from the same release page):

bash uv tool install https://github.com/bethington/ghidra-mcp/releases/download/v7.0.0/ghidra_mcp_bridge-7.0.0-py3-none-any.whl

5. Point your MCP client at it, using the absolute path (which bridge-mcp-ghidra, or where.exe bridge-mcp-ghidra on Windows):

json { "mcpServers": { "ghidra-mcp": { "command": "/home/<you>/.local/bin/bridge-mcp-ghidra" } } }

On Windows: "command": "C:\\Users\\<you>\\.local\\bin\\bridge-mcp-ghidra.exe". A client launched from a GUI or a service does not see your shell's PATH, so a bare bridge-mcp-ghidra fails with spawn ENOENT.

Open a program in Ghidra and ask your AI tool to list its functions. Screenshots of steps 2-3: docs/INSTALL_GUI.md. Building from source, Docker, the HTTP transports and every bridge flag are further down.

Which version should I run? Tagged releases (7.0.0, 7.1.0, ...) are stable. Release candidates and main are beta: feature-complete and live-tested, but shapes can still change before final. dev is experimental: tools are merged, renamed and refactored there freely, so build nothing on its API.

Why Ghidra MCP?

Most Ghidra MCP implementations give you a handful of read-only tools and call it a day. This project is different — it was built by a reverse engineer who uses it daily on real binaries, not as a demo.

• 219 MCP tools — 3x more than any competing implementation. Not just read operations — full write access for renaming, typing, commenting, structure creation, script execution, P-code emulation, and live debugging.
• Battle-tested AI workflows — Proven documentation workflows (V5) refined across hundreds of functions. Includes step-by-step prompts, Hungarian notation reference, batch processing guides, and orphaned code discovery.
• Production-grade reliability — Atomic transactions, batch operations (93% API call reduction), configurable timeouts, and graceful error handling. No silent failures.
• Cross-binary documentation transfer — SHA-256 function hash matching propagates documentation across binary versions automatically. Document once, apply everywhere.
• Full Ghidra Server integration — Connect to shared Ghidra servers, manage repositories, version control, checkout/checkin workflows, and multi-user collaboration.
• Headless and GUI modes — Run with or without the Ghidra GUI. Docker-ready for CI/CD pipelines and automated analysis at scale.
• Opinionated by design — v5.0 moves naming conventions, type safety, and documentation standards into the tool layer. AI agents and human engineers produce consistent output without style guides in every prompt.

Convention Enforcement

You've been there: six months into a project you find ProcessItem, process_items, handleItem, and ItemProc in the same codebase — four functions doing the same thing, named by four different sessions or engineers with no shared contract. Fixing it takes longer than it should, and the problem will happen again.

v5.0 moves conventions from "things to remember" into the tool layer, where they can actually be enforced.

For AI agents, this means consistent output across every session, every model, every run — without pasting a style guide into every prompt. The tool knows the rules; the model just needs to make the call.

For teams, it eliminates the entire class of review comment that says "that's not our naming convention." Convention arbitration stays in the tool, not in code review.

For solo work at scale, analyze_function_completeness gives you a 0–100% score that measures honestly: structural deductions (unfixable compiler artifacts) are forgiven in your effective score, log-scaling prevents one bad category from burying everything else, and tiered plate comment quality means you know exactly what's missing and why.

🌟 Features

Core MCP Integration

• Full MCP Compatibility — Complete implementation of Model Context Protocol
• 219 MCP tools — Comprehensive API surface covering every aspect of binary analysis
• Production-Ready Reliability — Atomic transactions, batch operations, configurable timeouts
• Real-time Analysis — Live integration with Ghidra's analysis engine

Compatibility note: MCP tool names are normalized for GitHub Copilot CLI and CAPI validation. Exposed tool names use lowercase letters, digits, underscores, and hyphens only; nested HTTP paths such as /debugger/status are advertised as names like debugger_status_2 when needed to avoid collisions with static bridge tools.

Binary Analysis Capabilities

• Function Analysis — Decompilation, call graphs, cross-references, completeness scoring
• Data Flow Analysis — PCode-graph value propagation (forward / backward) from any variable or register
• Data Structure Discovery — Struct/union/enum creation with field analysis and naming suggestions
• String Extraction — Regex search, quality filtering, and string-anchored function discovery
• Import/Export Analysis — Symbol tables, external locations, ordinal import resolution
• Memory & Data Inspection — Raw memory reads, byte pattern search, array boundary detection
• Cross-Binary Documentation — Function hash matching and documentation propagation across versions

Dynamic Analysis (v5.4.0)

• P-code Emulation — Run any function in isolation via Ghidra's EmulatorHelper; brute-force API hash resolution in milliseconds
• Live Debugger Integration — 16 /debugger/* endpoints over Ghidra's TraceRmi framework (GUI plugin only; dbgeng on Windows PE, gdb/lldb otherwise): launch, interrupt/resume, step into/over/out, breakpoints, registers, memory reads, stack traces, ASLR-aware static↔dynamic address translation. The bridge can also proxy 22 debugger_* tools to an external debugger server; they are opt-in (see below)

AI-Powered Reverse Engineering Workflows

• Function Documentation Workflow V5 — 7-step process for complete function documentation with Hungarian notation, type auditing, and automated verification scoring
• Batch Documentation