HopperPyMCP
A FastMCP server plugin for the Hopper disassembler that enables AI assistants to analyze binary files, disassemble procedures, generate call graphs, search strings, and manage reverse engineering tasks. Provides comprehensive binary analysis capabilities including decompilation, annotation tools, and reference tracking through natural language interactions.
README
HopperPyMCP - FastMCP Server for Hopper Disassembler
A FastMCP server plugin for the Hopper disassembler that provides powerful analysis tools through the Model Context Protocol (MCP). This plugin allows you to analyze binary files, disassemble procedures, manage documents, and more through AI assistants.
Features
- 🔍 Binary Analysis: Analyze segments, procedures, and data structures
- 🛠️ Disassembly & Decompilation: Get detailed assembly and pseudo-code output
- 📊 Call Graph Generation: Visualize function relationships and program flow
- 🔗 Reference Analysis: Track memory references and cross-references
- 📝 Annotation Tools: Add names, comments, and type information
- 🗂️ Document Management: Handle multiple executable files
- 🔍 String Search: Advanced regex-based string searching
Quick Installation
The installation process automatically detects your Python environment (conda, uv, venv, or system Python) and configures everything for you:
# Simple one-command installation
python install.py
That's it! The script will:
- ✅ Detect your Python environment automatically
- ✅ Install required dependencies (fastmcp)
- ✅ Configure the script with correct Python paths
- ✅ Install to the appropriate Hopper Scripts directory
Supported Environments
- Conda environments (including miniconda/anaconda)
- UV virtual environments
- Python venv/virtualenv
- System Python installations
- macOS and Linux platforms
If you use an environment like conda, uv, or virtualenv, run the install script from within a new environment, since dependencies will be installed by install.py.
Manual Installation Options
Dry Run (Preview Changes)
# See what would be installed without making changes
python install.py --dry-run
Force Installation
# Overwrite existing installation without prompting
python install.py --force
Uninstallation
Remove the plugin cleanly:
# Remove the installation
python uninstall.py
# Preview what would be removed
python uninstall.py --dry-run
# Remove without confirmation
python uninstall.py --confirm
Usage in Hopper
Once installed, the FastMCP server will be available as a script in Hopper.
Starting the Server
After running the script in Hopper, you'll need to launch the MCP server through the Python prompt:
-
First Time Setup - Cache Strings (Recommended)
Due to slow Hopper string APIs, the plugin creates optimized string caches for better performance. This process takes about 5-10 minutes per document and saves caches alongside your Hopper document saves.
In the Hopper Python prompt, paste:
cache_strings()Wait for caching to complete, then launch the server:
launch_server() -
Quick Start (Skip Caching)
To start immediately without caching (slower string searches):
launch_server() -
Subsequent Uses
If you've already cached strings for your documents:
launch_server()
The server will run on http://localhost:42069/mcp/ and provide the following tools:
Document Management
get_all_documents()- Get information about all currently opened documents (Hopper-analyzed binaries)get_current_document()- Get information about the current document with its doc_idset_current_document(doc_id)- Set the current document by doc_idrebase_document(new_base_address_hex)- Rebase the current document to a new base address
Core Analysis Tools
list_all_segments()- List all segments in the current document with basic informationget_address_info(address_or_name_list)- Get comprehensive information about multiple addresses/names including segment, section, type, procedure info, and references
Search and Discovery
search_names_regex(regex_pattern, segment_name, search_type, max_results)- Search for names matching a regex pattern in a specific segmentsearch_strings_regex(regex_pattern, segment_name, max_results)- Search for strings matching a regex pattern in a specific segmentget_string_at_addr(address_hex)- Get the string content at a specific address using the cached strings list
Disassembly & Decompilation
disassemble_procedure(address_or_name)- Disassemble a procedure into assembly language instructionsdecompile_procedure(address_or_name)- Decompile a procedure to C language code
Call Graph Generation
get_call_graph(start_addr_hex, direction, max_depth)- Return the call graph starting from a specific address
Name and Symbol Analysis
get_demangled_name(address_or_name)- Get the demangled name at a specific address or for a given name
Comments and Annotations
get_comment_at_address(address_hex)- Get the comment at a specific addressset_comment_at_address(address_hex, comment)- Set a comment at a specific addressset_name_at_address(address_hex, name)- Set a name/label at a specific addressmark_data_type_at_address(address_hex, data_type, length)- Mark data type at a specific address
Requirements
- Python 3.8+
- Hopper Disassembler v4 or v5
- FastMCP library (automatically installed)
File Structure
HopperPyMCP/
├── install.py # Main installation script
├── uninstall.py # Uninstallation script
├── fastmcp_server.py # Current working version
├── fastmcp_server_template.py # Template with placeholders
├── requirements.txt # Python dependencies
├── tests/ # Test suite
└── README.md # This file
Troubleshooting
Installation Issues
Problem: fastmcp import fails after installation
# Solution: Manually install dependencies
pip install fastmcp
# or for conda:
conda install -c conda-forge fastmcp
Problem: Permission denied when writing to Hopper directory
# Solution: Check Hopper directory permissions
ls -la ~/Library/Application\ Support/Hopper/Scripts/ # macOS
ls -la ~/GNUstep/Library/ApplicationSupport/Hopper/Scripts/ # Linux
Problem: Wrong Python environment detected
# Solution: Activate the correct environment first
conda activate your-environment # for conda
source your-venv/bin/activate # for venv
# Then run install.py
Runtime Issues
Problem: Script not appearing in Hopper
- Verify installation path is correct for your platform
- Check Hopper Scripts directory exists and is readable
- Restart Hopper after installation
Problem: Import errors when running in Hopper
- The installation should handle Python path configuration automatically
- If issues persist, check that the installed script has the correct paths
Platform-Specific Notes
macOS: Scripts install to ~/Library/Application Support/Hopper/Scripts/
Linux: Scripts install to ~/GNUstep/Library/ApplicationSupport/Hopper/Scripts/
Development
Running Tests
# Run the test suite
python -m pytest tests/
Development Installation
For development, you might want to symlink instead of copy:
# Manual symlink for development
ln -s $(pwd)/fastmcp_server.py ~/Library/Application\ Support/Hopper/Scripts/
Support
For issues and questions:
- Check the troubleshooting section above
- Review the test files for usage examples
- Open an issue on the project repository
Note: This plugin requires Hopper's built-in Python interpreter. The installation script automatically configures the necessary Python paths for seamless integration.
推荐服务器
Baidu Map
百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。
Playwright MCP Server
一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。
Magic Component Platform (MCP)
一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。
Audiense Insights MCP Server
通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。
VeyraX
一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。
graphlit-mcp-server
模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。
Kagi MCP Server
一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。
e2b-mcp-server
使用 MCP 通过 e2b 运行代码。
Neon MCP Server
用于与 Neon 管理 API 和数据库交互的 MCP 服务器
Exa MCP Server
模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。