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BinAssistMCP

Comprehensive Model Context Protocol (MCP) server for Binary Ninja with AI-powered reverse engineering capabilities

Summary

BinAssistMCP is a powerful bridge between Binary Ninja and Large Language Models (LLMs) like Claude, providing comprehensive reverse engineering tools through the Model Context Protocol (MCP). It enables AI-assisted binary analysis by exposing Binary Ninja's advanced capabilities through Server-Sent Events (SSE) and Streamable HTTP transports.

Key Features

  • MCP 2025-11-25 Compliant: Full support for tool annotations, resources, and prompts

  • Dual Transport Support: SSE (Server-Sent Events) and Streamable HTTP transports

  • 36 Consolidated Tools: Streamlined Binary Ninja API wrapper with unified tool design

  • 8 MCP Resources: Browsable, cacheable binary metadata

  • 7 Guided Prompts: Pre-built workflows for common reverse engineering tasks

  • Multi-Binary Sessions: Concurrent analysis of multiple binaries with intelligent context management

  • Analysis Caching: LRU cache with binary-scoped invalidation for improved performance

  • Async Task Support: Non-blocking execution for long-running operations

  • Thread-Safe: RLock-based synchronization for concurrent access

  • Auto-Integration: Seamless Binary Ninja plugin with automatic startup capabilities

Use Cases

  • AI-Assisted Reverse Engineering: Leverage LLMs for intelligent code analysis and documentation

  • Protocol Analysis: Trace network data flows and reconstruct protocol structures

  • Vulnerability Research: Systematic security audits with guided workflows

  • Automated Binary Analysis: Script complex analysis workflows with natural language

  • Code Understanding: Generate comprehensive documentation and explanations


Related MCP server: Binary Ninja MCP

Architecture

src/binassist_mcp/ ├── server.py # FastMCP server - SSE/Streamable HTTP transport, tool registration ├── tools.py # Binary Ninja API wrapper - 36 MCP tools ├── plugin.py # Binary Ninja plugin integration ├── context.py # Thread-safe multi-binary session management ├── config.py # Pydantic configuration with Binary Ninja settings ├── prompts.py # 7 guided workflow prompts ├── resources.py # 8 MCP resource definitions ├── cache.py # LRU analysis cache with invalidation ├── tasks.py # Async task manager for long-running operations ├── logging.py # Binary Ninja logging integration └── utils.py # Utility functions __init__.py # Plugin entry point (root level)

Tools (36 Total)

BinAssistMCP provides 36 tools organized into functional categories. Tools include MCP annotations (readOnlyHint, idempotentHint) to help clients make informed decisions.

Binary Management

Tool

Description

list_binaries

List all loaded binary files

get_binary_status

Check analysis status and metadata

update_analysis_and_wait

Force analysis update and wait for completion

Code Analysis (Consolidated)

Tool

Description

get_code

Unified code retrieval - supports formats: decompile, hlil, mlil, llil, disasm, pseudo_c

get_function_low_level_il

Get Low-Level IL for a function

analyze_function

Comprehensive function analysis with control flow and complexity metrics

get_basic_blocks

Get basic block information for control flow analysis

get_function_stack_layout

Get stack frame layout with variable offsets

Cross-References (Consolidated)

Tool

Description

xrefs_tool

Unified cross-references - actions: refs_to, refs_from, call_graph

Comments (Consolidated)

Tool

Description

comments_tool

Unified comment management - actions: get, set, list, remove, set_function

Variables (Consolidated)

Tool

Description

variables_tool

Unified variable management - actions: list, create, rename, set_type

Types (Consolidated)

Tool

Description

types_tool

Unified type management - actions: create, create_enum, create_typedef, create_class, add_member, get_info, list

get_classes

List all classes and structures

Function Discovery

Tool

Description

get_functions

List all functions with metadata (paginated)

search_functions_by_name

Find functions by name pattern

get_functions_advanced

Advanced filtering by size, complexity, parameters

search_functions_advanced

Multi-target search (name, comments, calls, variables)

get_function_statistics

Comprehensive statistics for all functions

Symbol Management

Tool

Description

rename_symbol

Rename functions and data variables

batch_rename

Rename multiple symbols in one operation

get_namespaces

List namespaces and symbol organization

Binary Information

Tool

Description

get_imports

Import table grouped by module

get_exports

Export table with symbol information

get_strings

String extraction with filtering

search_strings

Search strings by pattern

get_segments

Memory segment layout

get_sections

Binary section information

Data Analysis

Tool

Description

create_data_var

Define data variables at addresses

get_data_vars

List all defined data variables

get_data_at_address

Read and analyze raw data

search_bytes

Search for byte patterns in binary

Navigation

Tool

Description

get_current_address

Get current cursor position with context

get_current_function

Identify function at current address

Task Management

Tool

Description

get_task_status

Check status of async operations

list_tasks

List all pending/running tasks

cancel_task

Cancel a running task


MCP Resources (8 Total)

Resources provide browsable, cacheable data that clients can access without tool calls.

URI Pattern

Description

binassist://{filename}/triage_summary

Complete binary overview

binassist://{filename}/functions

All functions with metadata

binassist://{filename}/imports

Import table

binassist://{filename}/exports

Export table

binassist://{filename}/strings

String table

binja://{filename}/info

Binary metadata (arch, platform, entry point)

binja://{filename}/segments

Memory segments with permissions

binja://{filename}/sections

Binary sections


MCP Prompts (7 Total)

Pre-built prompts guide LLMs through structured analysis workflows.

Prompt

Arguments

Description

analyze_function

function_name, filename

Comprehensive function analysis workflow

identify_vulnerability

function_name, filename

Security audit checklist (memory safety, input validation, crypto)

document_function

function_name, filename

Generate Doxygen-style documentation

trace_data_flow

address, filename

Track data dependencies and taint propagation

compare_functions

func1, func2, filename

Diff two functions for similarity analysis

reverse_engineer_struct

address, filename

Recover structure definitions from usage patterns

trace_network_data

filename

Trace POSIX/Winsock send/recv for protocol analysis

Example: Network Protocol Analysis

The trace_network_data prompt guides analysis of network communication:

  1. Identify Network Functions: Finds POSIX (send/recv/sendto/recvfrom) and Winsock (WSASend/WSARecv) calls

  2. Trace Call Stacks: Maps application handlers down to network I/O

  3. Analyze Buffers: Identifies protocol structures (headers, length fields, TLV encoding)

  4. Reconstruct Protocols: Generates C struct definitions for message formats

  5. Security Assessment: Checks for buffer overflows, integer issues, information disclosure


Installation

Prerequisites

  • Binary Ninja: Version 4000 or higher

  • Python: 3.8+ (typically bundled with Binary Ninja)

  • Platform: Windows, macOS, or Linux

NOTE: Windows users should start with: BinAssistMCP on Windows

  1. Open Binary Ninja

  2. Navigate to ToolsManage Plugins

  3. Search for "BinAssistMCP"

  4. Click Install

  5. Restart Binary Ninja

Option 2: Manual Installation

# Clone the repository git clone https://github.com/jtang613/BinAssistMCP.git cd BinAssistMCP # Install dependencies pip install -r requirements.txt

Copy to your Binary Ninja plugins directory:

Platform

Path

Windows

%APPDATA%\Binary Ninja\plugins\

macOS

~/Library/Application Support/Binary Ninja/plugins/

Linux

~/.binaryninja/plugins/


Configuration

Binary Ninja Settings

Open EditPreferencesbinassistmcp:

Setting

Default

Description

server.host

localhost

Server bind address

server.port

9090

Server port

server.transport

streamablehttp

Transport: streamablehttp or sse

binary.max_binaries

10

Maximum concurrent binaries

plugin.auto_startup

true

Auto-start server on file load

Environment Variables

export BINASSISTMCP_SERVER__HOST=localhost export BINASSISTMCP_SERVER__PORT=9090 export BINASSISTMCP_SERVER__TRANSPORT=streamablehttp export BINASSISTMCP_BINARY__MAX_BINARIES=10

Usage

Starting the Server

Via Binary Ninja Menu:

  1. ToolsBinAssistMCPStart Server

  2. Check log panel for: BinAssistMCP server started on http://localhost:9090

Auto-Startup: Server starts automatically when Binary Ninja loads a file (configurable).

Connecting MCP Clients

Streamable HTTP (Default):

http://localhost:9090/mcp

Server-Sent Events:

http://localhost:9090/sse

Claude Desktop Configuration

Add to your Claude Desktop MCP configuration (claude_desktop_config.json):

{ "mcpServers": { "binassist": { "url": "http://localhost:9090/mcp" } } }

Integration Examples

Basic Function Analysis

User: "Analyze the main function and explain what it does" Claude uses: 1. get_functions() - find main 2. get_code(format='decompile') - get readable code 3. xrefs_tool(action='refs_from') - find called functions 4. analyze_function() - get complexity metrics

Vulnerability Research

User: "Find buffer overflow vulnerabilities in input handling functions" Claude uses: 1. search_functions_advanced(search_in='calls') - find memcpy/strcpy callers 2. get_code(format='decompile') - examine implementations 3. variables_tool(action='list') - check buffer sizes 4. comments_tool(action='set') - document findings

Protocol Reverse Engineering

User: "Analyze the network protocol used by this binary" Claude uses the trace_network_data prompt: 1. Identifies send/recv call sites 2. Traces data flow from handlers to network I/O 3. Reconstructs message structures 4. Checks for network vulnerabilities

Troubleshooting

Server Issues

Problem

Solution

Server won't start

Check port 9090 availability, verify dependencies

Connection refused

Ensure server is running, check firewall settings

Tools return errors

Wait for analysis completion, verify binary is loaded

Performance

  • Slow decompilation: Results are cached; second request is faster

  • Memory usage: Reduce max_binaries setting

  • Long operations: Check task status with get_task_status

Logs

Check Binary Ninja's Log panel for detailed error messages.


Contributing

  1. Fork the repository

  2. Create a feature branch

  3. Follow existing code patterns (Pydantic models, type hints, docstrings)

  4. Test with multiple binary types

  5. Submit a pull request


License

This project is licensed under the MIT License - see the LICENSE file for details.

-
security - not tested
A
license - permissive license
-
quality - not tested

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