@jshookmcp/jshook

A search-first, profile-aware reverse-engineering workspace for AI agents.

Hook the page, capture the network, deobfuscate the bundle, disassemble the WASM, instrument the process — and let one MCP server keep the whole attack surface in reach without drowning the model in schemas.

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What's different · Capabilities · Use cases · Highlights · Transport · Registry · Architecture · Build

Documentation · Getting Started · Configuration · Tool Reference

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What makes jshook different

Most MCP servers for JS analysis expose a handful of hand-rolled tools or wrap a single browser engine. jshook is closer to an operating system for front-end reverse engineering — 34 self-discovered domains, a search-first meta-tool that keeps token cost under control, and runtime recovery that survives broken pages and dropped sessions:

• Search-first, profile-aware. The search profile loads about 3K tokens of tool metadata; the full profile exposes all 723 tools at around 40K tokens. Agents move between them as the task grows — search → workflow → full — instead of drowning in schemas from the first turn.
• Runtime recovery and session isolation. Streamable HTTP sessions restore activated domains, browser attach state, and coverage state after reconnects; per-client browser-side state stays isolated so two agents cannot trample each other's CDP sessions.
• Full-stack browser automation. Chromium and Camoufox via CDP with anti-detection, an explicit-input CAPTCHA solver (no built-in page/feature probing), a self-signed HTTPS interception CA on demand, and HTTP/2 frame building.
• Real reverse engineering, not string searches. WASM disassembly via Binaryen, Frida/Ghidra/IDA bridges, native FFI scanning, hardware breakpoints, PE introspection, GraphQL/Burp Suite proxy bridges, and AST transforms — not a single regex call wrapped as a tool.
• Dynamic extensibility. Hot-reload plugins, declarative workflows, and auto-discovery keep the server growing without a redeploy.

Capability overview

A scan of what's in the box. Each row links to the detailed Capability overview below.

Use cases

Quick start

No global install needed — add to your MCP client config and you're ready.

Claude Desktop / Cursor (claude_desktop_config.json):

{
  "mcpServers": {
    "jshook": {
      "command": "npx",
      "args": ["-y", "@jshookmcp/jshook@latest"],
      "env": {
        "MCP_TOOL_PROFILE": "search",
        "npm_config_omit": "optional"
      }
    }
  }
}

(Windows: use npx.cmd absolute path if npx is not found.)

This lightweight configuration skips optional ONNX, Z3, Binaryen, Camoufox, and Playwright packages. Remove npm_config_omit when those full-profile runtimes are required.

Share one daemon across multiple agents

The default stdio configuration starts one full jshook process per MCP host. To share the embedding model, browser runtime, and caches, start one local Streamable HTTP daemon:

pnpm build
pnpm daemon

Vector search defaults to off for per-client stdio processes and on (lazy-loaded) for the shared HTTP daemon. Set SEARCH_VECTOR_ENABLED=false when lexical search is sufficient.

Then point every MCP client at http://127.0.0.1:3000/mcp using its HTTP/URL server configuration. Each client receives its own MCP session and response route while heavyweight runtime resources remain in one process. Keep the default loopback bind; set MCP_AUTH_TOKEN before exposing the endpoint beyond localhost.

Promote a profile as the task grows

{
  "env": {
    "MCP_TOOL_PROFILE": "search"     // start here, ~3K tokens of metadata
  }
}

Switch MCP_TOOL_PROFILE to workflow once you start chaining composite scripts, or to full when you need every tool. coverage_report shows the active set on demand.

Highlights