Ghidralens

Name: Ghidralens
Author: hellosverre

by hellosverreversion 0.1.1i★ –iRuns on your computer

Registry nameio.github.hellosverre/ghidralens

Install

Overview

Description from the maker (original English)

Interactive Ghidra views in your AI client: decompile, rename, and navigate a binary.

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

User voiceiNo reviews yetReviews open together with accounts in a later step
Our basic checksi1 of 1 passedChecked from public information; code not scanned yet
UsageiNot measured yet★ –

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

Connection: Runs on your computer
Transport: stdio
Category: Other
You need to fill in: GHIDRALENS_TOKEN

Install

Pick the AI app you use, then copy the settings.

Before you install

Basic checks: 1 of 1 passed
Runs on your computer with your user’s permissions (files, network, apps).
You fill in yourself: GHIDRALENS_TOKEN, GHIDRALENS_BRIDGE_URL

Values marked secret are keys to your account. Never share them or paste them into a chat.

You need

npmNode.js installed (for the npx command)

Which app do you use?

ClaudeClaude CodeCursorVS CodeChatGPT

Pick your app above. We remember it, so next time the button says “Install in …”.

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

{
  "mcpServers": {
    "ghidralens": {
      "command": "npx",
      "args": [
        "-y",
        "ghidralens"
      ],
      "env": {
        "GHIDRALENS_TOKEN": "your-value",
        "GHIDRALENS_BRIDGE_URL": "your-value"
      }
    }
  }
}

Run this in your terminal

claude mcp add ghidralens --env GHIDRALENS_TOKEN=your-value --env GHIDRALENS_BRIDGE_URL=your-value -- npx -y ghidralens

Fill in the empty values before running it.

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "ghidralens": {
      "command": "npx",
      "args": [
        "-y",
        "ghidralens"
      ],
      "env": {
        "GHIDRALENS_TOKEN": "your-value",
        "GHIDRALENS_BRIDGE_URL": "your-value"
      }
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "ghidralens": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "ghidralens"
      ],
      "env": {
        "GHIDRALENS_TOKEN": "your-value",
        "GHIDRALENS_BRIDGE_URL": "your-value"
      }
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.

Your choice stays on this device in a cookie; no account needed.

Values you fill in

GHIDRALENS_TOKEN secret required env
Shared secret printed by the PyGhidra bridge on startup. Start the bridge first: python bridge/serve.py --binary
GHIDRALENS_BRIDGE_URL env
Where the PyGhidra bridge is listening. Defaults to http://127.0.0.1:8799

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 6, 2026

✓ Pass
Maker matches the repo
The registry name was verified with the GitHub account hellosverre, which owns the repo
… Not checked yet
Still maintained
We have not read this repo from GitHub yet
… Not checked yet
Has a licence
We have not read this repo from GitHub yet
– Not applicable
Endpoint responds
This one runs on your computer; there is no internet endpoint
– Not applicable
Sign-in with OAuth
Runs on your computer and uses local settings instead
… Not checked yet
No hidden instructions in tool descriptions
Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Otheri

More stars than 0% of the other 32531 servers in this category
Published to the registry more recently than 31% of the other 32531 servers in this category
Basic checks equal to or better than 100% of the other 32531 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is Ghidralens safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

You need to fill in: GHIDRALENS_TOKEN

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed –, and the latest version (0.1.1) reached the registry 2 months ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Node.js on your computer.

What can I use instead?

In the same category: Spec Driven Development, Remote Desktop Commander, Reelsaw

Alternatives

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Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

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Runs on your computer★ 440MITUpdated 14 months ago

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README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

GhidraLens

Ghidra, rendered inside your AI client. Click a symbol to rename it. Click a call to follow it.

Every Ghidra MCP server so far returns text. The model can read it; you cannot navigate it. GhidraLens returns the same analysis as an interactive view — built on MCP Apps (io.modelcontextprotocol/ui), the extension that lets a server ship real HTML into the conversation.

You and the model are looking at the same live program. Rename a variable by clicking it and the model's next decompile sees the new name.

That is a real screenshot: where.exe, decompiled by Ghidra, every identifier carrying the address it came from.

What you get

View	What it does
Decompiler	Ghidra's C output as a live token stream — every identifier carries its address and its kind. Click a local to rename it, click a call to follow it. Callers, callees and variables in a sidebar.
Function browser	Every function in the binary, filterable and sortable by address, name, size or caller count. Click a row to decompile it.
Call graph	Callers to the left, callees to the right, the function you asked about in the middle. Click any node to recenter.

Function browser

Call graph

Ten tools total. Three open views; the rest are lookups and writes, including two the model never sees — they exist only so a click in a view can fire them.

How it fits together

  MCP client  ──stdio──▶  server/  ──HTTP──▶  bridge/  ──JPype──▶  Ghidra (JVM)

(Claude, TypeScript PyGhidra program stays Cursor, …) MCP server session resident ▲ │ ui:// HTML in a sandboxed iframe └── ui/ three self-contained views

The bridge is a separate long-lived process on purpose. Ghidra's auto-analysis is the expensive step, and it happens once. Measured on a 64 KB Windows system utility (198 functions):


First open, with analysis	25 s
Re-open the same binary	0.3 s
Decompile one 2 KB function	0.4 s
87-node call graph	< 0.1 s

Restart the MCP server or the client and the analysed program is still there.

Setup

Prerequisites: Ghidra 11.3+, a JDK 21+, Python 3.9–3.13 (not 3.14 — JPype has no wheel for it yet), Node 20+. See bridge/setup.py.md — the Python side is fussy and that file covers every way it goes wrong. GhidraLens finds a JDK for you if JAVA_HOME is unset, which covers the usual "installed Java, shell has not restarted" case.

git clone https://github.com/hellosverre/ghidralens

cd ghidralens npm install npm run build

Then start the bridge on the binary you want to look at:

python bridge/serve.py --binary /path/to/target.exe

It prints a token. Put that, and the path to the built server, into your MCP client config:

"mcpServers": { "ghidralens": { "command": "npx", "args": ["-y", "ghidralens"], "env": { "GHIDRALENS_BRIDGE_URL": "http://127.0.0.1:8799", "GHIDRALENS_TOKEN": "paste-the-printed-token-here" } } } }

Running from a clone instead? Point command at node and args at /absolute/path/to/ghidralens/server/dist/index.js.

Then ask your client: *"decompile the function that handles license validation"*.

Also listed in the official MCP Registry as io.github.hellosverre/ghidralens.

Editing the config by hand? Quit the client first — properly, including any

system-tray icon. Claude Desktop keeps its own copy of

claude_desktop_config.json in memory and writes it back over yours when it

exits, so an edit made while it is running silently disappears on the next

restart. Editing through Settings → Developer → Edit Config avoids the race

entirely.

Tools

Tool	Visible to	Renders
`open_binary`	model	—
`program_info`	model	—
`decompile`	model + view	Decompiler
`list_functions`	model + view	Function browser
`call_graph`	model + view	Call graph
`find_strings`	model	—
`xrefs_to`	model + view	—
`rename_symbol`	model + view	—
`add_comment`	view only	—
`save_program`	model	—

add_comment is hidden from the model deliberately. Visibility is how MCP Apps separates "the agent may do this" from "a click may do this"; keeping write tools out of the model's list keeps it short and stops the model from renaming things on its own initiative.

Renames and comments live in memory until save_program writes them into the Ghidra project — after which they show up in the Ghidra GUI like any other edit.

Developing the views without Ghidra

npm run dev:ui

open http://localhost:5173/dev/harness.html

ui/dev/harness.ts is a real MCP Apps host — it runs the SDK's AppBridge against the view in an iframe, so the ui/initialize handshake, the opening ui/notifications/tool-result, and every tools/call a click fires all go over real postMessage JSON-RPC. There is a message trace down the right-hand side and a host-theme switch, because the views have to look right in both.

Two data sources, switchable in the toolbar:

fixtures — no Ghidra needed, nothing to install
live bridge — proxies to a running bridge, so you develop against a real analysed program

Use live before you trust anything. Fixtures are tidy; real output is a 400-line function with 56 locals and an 87-node call graph, and that is where layout actually breaks.

Running it on a local model

Reverse engineering is exactly the work people would rather not send to a hosted model, so agent/ollama-agent.mjs is a small MCP host that puts GhidraLens behind Ollama instead. No API key, nothing leaves the machine.

OLLAMA_MODEL=qwen3:14b node agent/ollama-agent.mjs "what does this binary do?"

It respects _meta.ui.visibility, so the app-only tools stay hidden from the model — the same separation a graphical client enforces. A ~9B model is enough to orient itself with find_strings and list_functions; a 14B is noticeably better at reading decompiled C.

Tests

Suite	Needs Ghidra	Covers
`node server/smoke.mjs`	no	MCP surface: tools, `ui://` resources, tool visibility, graceful failure with no bridge
`python bridge/test_serve.py`	no	Bridge auth, CSRF rejection, routing, input validation
`python bridge/test_session.py`	yes	Every Ghidra call: analysis, caching, decompiler tokens, imports, renames, writes
`node server/live.mjs`	yes (bridge running)	The whole chain, and that every payload matches the shape the views index into

The first two are what CI can run. test_session.py is the one that matters after touching bridge/session.py — it is the only thing that proves the Ghidra API calls are right, and it caught three real bugs the day it was written.

Containerising it

The Dockerfile builds the server and views for clients or registries that want to start it themselves. One thing to get right:

CMD ["node", "server/dist/index.js"]     # correct

CMD ["npm", "run", "start"] # breaks the protocol

A stdio MCP server speaks JSON-RPC on stdout, and npm run / pnpm run print the script banner there first:

> ghidralens@0.1.1 start

node server/dist/index.js

Those lines land in the stream ahead of the handshake and the client gives up mid-initialize. The symptom is unhelpful - the container builds, starts, exits cleanly, and the client just reports no tools - so it is worth not stepping on. Invoke node directly.

Real analysis still needs the bridge on the host: 127.0.0.1 inside a container is the container, so point GHIDRALENS_BRIDGE_URL at host.docker.internal or a real address.

Security

The bridge binds 127.0.0.1 only, requires a per-run token in X-GhidraLens-Token, and rejects any request carrying an Origin or Referer header — so a page open in your browser cannot reach your decompiler. It has no multi-user model and is not meant to be exposed; --host refuses anything but loopback.

Analysing a binary does not execute it, but Ghidra will happily open malware. Use the same isolation you would use for any other RE work.

Licence

MIT.

Ghidralens

Overview

PopNx MCP’s three pillars

What you can do with it

Install

Before you install

Values you fill in

What it can do

Basic checksi

Maker matches the repo

Still maintained

Has a licence

Endpoint responds

Sign-in with OAuth

No hidden instructions in tool descriptions

Compared with others in Otheri

Common questions

Alternatives

Spec Driven Development

Remote Desktop Commander

Reelsaw

README from the maker

GhidraLens

What you get

Function browser

Call graph

How it fits together

Setup

Tools

Developing the views without Ghidra

open http://localhost:5173/dev/harness.html

Running it on a local model

Tests

Containerising it

Security

Licence