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JSHookMCP
735 reverse-engineering tools for AI agents in 3K tokens
Each reverse-engineering tool stops at one layer: Playwright at the DOM, Ghidra at static binaries, Frida at a live process. jshookmcp gives an AI agent one workspace across TLS keylog, DOM, JS AST, V8 Turbofan, WASM, Mojo IPC, native memory, ARM64 JNI and syscalls, linked into a causal evidence graph. 735 tools blow up any context window, so the default profile ships 8 meta-tools at ~3K tokens, activating domains on demand with a 30-minute TTL. 1.9K measured against 109K for the full surface.
Every reverse-engineering tool I tried lived on exactly one layer. A browser tool can read the DOM but not the V8 JIT that produced it. A debugger sees the process but not the HTTP/2 frame that triggered it. The analysis stayed manual, and an agent could not follow one signal across those boundaries.
jshookmcp started as a browser/CDP toolkit and grew downward: network and TLS keylog, DOM, JS AST, WASM, Mojo IPC, native memory, then an in-process ARM64 interpreter for Android JNI, then syscalls. The point is that a finding on one layer can be linked back to the layer that caused it, in one evidence graph instead of five terminals.
The hard part turned out to be context. 735 tools is roughly 109K tokens of schema, which no agent can afford. So the default profile exposes 8 meta-tools and a local search tier (BM25 + ONNX embeddings + RRF), and domains activate on demand with a 30-minute TTL. That lands at about 1.9K tokens.
It is AGPL-3.0. Ask me anything about the JNI interpreter or how the cross-domain graph is assembled.
About JSHookMCP on Product Hunt
“735 reverse-engineering tools for AI agents in 3K tokens”
JSHookMCP was submitted on Product Hunt and earned 0 upvotes and 1 comments, placing #320 on the daily leaderboard. Each reverse-engineering tool stops at one layer: Playwright at the DOM, Ghidra at static binaries, Frida at a live process. jshookmcp gives an AI agent one workspace across TLS keylog, DOM, JS AST, V8 Turbofan, WASM, Mojo IPC, native memory, ARM64 JNI and syscalls, linked into a causal evidence graph. 735 tools blow up any context window, so the default profile ships 8 meta-tools at ~3K tokens, activating domains on demand with a 30-minute TTL. 1.9K measured against 109K for the full surface.
On the analytics side, JSHookMCP competes within Developer Tools, Artificial Intelligence and GitHub — topics that collectively have 1M followers on Product Hunt. The dashboard above tracks how JSHookMCP performed against the three products that launched closest to it on the same day.
Who hunted JSHookMCP?
JSHookMCP was hunted by Jerry Tomas. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
For a complete overview of JSHookMCP including community comment highlights and product details, visit the product overview.
Jerry Tomas