Velociraptor MCP
Velociraptor MCP connects Large Language Models with MCP clients, providing capabilities for querying Windows artifacts and system information effectively.
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Created by:
May 07 2025
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What is Velociraptor MCP?
Velociraptor MCP is a specialized Protocol bridge designed to facilitate interaction between Large Language Models (LLMs) and MCP clients. It enables querying Windows artifacts, network connections, and system artifacts such as the USN journal. The setup involves API configuration, cloning the repository, testing the API, and connecting with MCP clients or desktop environments for automation and forensic tasks. It is especially useful for security investigations and system automation scenarios, allowing dynamic artifact targeting and data collection through LLM queries.
Who will use Velociraptor MCP?
- Cybersecurity Professionals
- Digital Forensics Analysts
- System Administrators
- Developers working on system automation and threat detection
How to use the Velociraptor MCP?
- Step1: Set up an API account following Velociraptor documentation
- Step2: Clone the mcp-velociraptor repository from GitHub
- Step3: Configure the API credentials in test_api.py and mcp_velociraptor_bridge.py
- Step4: Run test_api.py to ensure connectivity
- Step5: Connect the bridge to MCP client or desktop environment for querying and automation
Velociraptor MCP's Core Features & Benefits
The Core Features
- Exposing LLMs to MCP clients
- Querying Windows system artifacts
- System for network connections and process analysis
- Artifact collection targeting USN journal and network artifacts
The Benefits
- Enhanced automation of forensic and security tasks
- Dynamic querying with large language models
- Simplified integration for security investigations
- Improved system artifact collection and analysis
Velociraptor MCP's Main Use Cases & Applications
- Automated digital forensics investigations
- System threat hunting and malware analysis
- Network connection monitoring
- Artifact collection for incident response