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Binary Ninja MCP Server

MCP Server

Expose Binary Ninja analysis via the Model Context Protocol

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Updated Aug 12, 2025

About

A Python‑based MCP server that runs inside or headlessly with Binary Ninja, providing tools for renaming symbols, generating pseudo C/Rust code, retrieving IL and disassembly, and exposing binary metadata to external clients.

Capabilities

Resources
Access data sources
Tools
Execute functions
Prompts
Pre-built templates
Sampling
AI model interactions

demo

Overview

The BinaryNinja MCP server bridges the gap between powerful binary analysis and conversational AI assistants. By exposing a rich set of tools, resources, and prompts directly from Binary Ninja, it allows an AI model to interrogate a binary’s structure, query disassembly or high‑level representations, and even modify symbols—all through the Model Context Protocol. This eliminates the need for manual data extraction or custom scripts, enabling developers to ask high‑level questions about a binary and receive precise, context‑aware answers.

At its core, the server solves the problem of information silos in reverse engineering workflows. Traditionally, analysts must switch between Binary Ninja’s GUI, command‑line scripts, or third‑party tools to gather insights. The MCP server consolidates these capabilities into a single, network‑accessible interface that any AI client can consume. This unified access streamlines iterative analysis loops: an assistant can request a function’s pseudo‑C representation, rename it based on semantic clues, and immediately see the updated analysis reflected back in Binary Ninja.

Key features include a comprehensive toolset such as , , and various IL representations, which provide layered views of a function’s logic. Utility tools like , , and give quick overviews of binary metadata, while ensures that analysis remains current before any request is processed. The server also exposes resources via URI schemes (), allowing clients to retrieve structured data such as function lists or segment information without additional API calls.

Real‑world scenarios benefit from this integration in several ways. Security researchers can let an AI assistant walk through a malware sample, automatically generating annotated pseudo‑code and highlighting suspicious imports. Software engineers can use the server to refactor legacy binaries by renaming symbols on the fly and verifying changes through updated IL outputs. Continuous integration pipelines can incorporate the MCP server to validate binaries against security policies, automatically extracting triage summaries and export lists for audit purposes.

Integration with AI workflows is straightforward: a client such as Claude Desktop or Cherry Studio can be configured to connect via stdio or SSE, then send standard MCP requests. The server’s lightweight design means it can run in the background of a Binary Ninja session or as a headless service, making it suitable for both interactive desktop use and automated analysis environments. Its open‑source nature and Apache 2.0 license encourage community contributions, ensuring that new tools or resource types can be added as the reverse‑engineering ecosystem evolves.