Overview of cutterMCP

cutterMCP is a Model Context Protocol (MCP) server that bridges large language models with the powerful binary analysis capabilities of Cutter, a popular reverse‑engineering platform. By exposing Cutter’s decompilation engine, symbol management tools, and binary metadata through MCP, the server enables AI assistants to autonomously inspect, modify, and document executable files without manual intervention. This solves a key bottleneck for developers who rely on AI to generate insights about malware, firmware, or legacy software: the lack of a direct, programmatic interface to deep binary analysis.

The server provides a rich set of tools that mirror the most frequently used Cutter functions. Once connected, an AI client can:

• Decompile binaries into human‑readable pseudocode, allowing the model to reason about control flow and data structures.
• Rename methods and data automatically based on semantic analysis or user‑supplied conventions, improving the readability of the output.
• Enumerate methods, imports, and exports, giving the assistant a comprehensive view of the binary’s interface and internal organization.

These capabilities are delivered through MCP resources, prompts, and sampling interfaces that the client can invoke in a natural language style. The result is an AI workflow where the assistant can ask, “Show me all exported functions of this binary,” and receive a structured list without needing to manually launch Cutter or parse its UI.

Real‑world scenarios that benefit from cutterMCP include security researchers automating malware triage, firmware engineers reverse‑engineering IoT devices, and developers debugging legacy binaries. In each case, the AI can perform preliminary analysis—such as identifying suspicious imports or generating documentation—before a human analyst dives deeper. Because cutterMCP is built on the standard MCP SDK, it integrates seamlessly with any MCP‑compliant client, from Claude Desktop to custom Python scripts. The plugin architecture also means that developers can extend or customize the server’s behavior without touching the core code, making it adaptable to evolving analysis needs.

What sets cutterMCP apart is its tight coupling between AI intent and low‑level binary manipulation. Rather than merely providing static data, the server lets the assistant issue commands that alter the analysis state in Cutter itself. This bidirectional interaction enables iterative workflows: an AI can propose a rename, verify the effect in decompiled code, and refine its strategy—all within a single conversational loop. For developers building AI‑powered reverse‑engineering tools, cutterMCP offers a powerful, ready‑to‑use bridge that turns language models into proactive binary analysts.