Integrates with .env files for configuration, particularly for setting the SAFE_BASE directory to restrict file operations
Provides testing capabilities with pytest, allowing users to validate the functionality of the forensic toolkit
Server is built to be used with Python 3.10+ for digital forensics, enabling automated forensic investigations and report generation
MCP Forensic Toolkit
MCP Forensic Toolkit is a secure, AI-ready local server for digital forensics, built using the Model Context Protocol (MCP). It exposes semantically meaningful tools to analyze logs, verify file integrity, and generate audit-grade forensic reports. Designed for analysts and LLMs alike, it enables automated investigation with precision and safety.
Features
- Structured log triage using keyword-based scanning (
scan_syslog
) - File metadata extraction and SHA-256 hashing (
file_metadata
) - Recursive integrity scanning with directory hashing (
hash_directory
) - Correlation engine linking file modifications to log events (
correlate_file_and_logs
) - Human-readable forensic reporting (
generate_forensic_report
) - Secure access control via
SAFE_BASE
and sandboxed environment - Built-in LLM prompts for guided reasoning and forensic tasks
Screenshot
This example demonstrates a successful correlation analysis between a file and system log entries using the generate_forensic_report
tool:
Getting Started
Prerequisites
- Python 3.10+
- Poetry or pip
- MCP CLI (
pip install modelcontext
or follow setup guide) .env
file withSAFE_BASE
defined
Installation
Usage
Start the Server
server.py
is the entry point and defines all MCP tools, prompts, and resources.
Access via MCP Inspector
Use the MCP Inspector or visit:
You can then:
- Run tools (
scan_syslog
,file_metadata
, etc.) - Execute prompts for analysis
- View and inspect structured output
CLI Demo (Optional)
You can run a command-line demo as follows:
If correlation is found, output includes:
Otherwise:
Example Workflow
- Modify or inspect a file within
SAFE_BASE
. - Run
generate_forensic_report
or the CLI tool. - Use MCP Inspector or LLM to interpret results.
- Example match:
Environment Variables
Variable | Description |
---|---|
SAFE_BASE | Restricts all file operations to this path. |
Example .env.example
:
Security Considerations
- All tools validate paths against
SAFE_BASE
- System logs are accessed in a read-only way
- Tools gracefully handle permission errors and malformed inputs
- CLI interface avoids unsafe globbing or directory traversal
Testing
Run unit tests:
Or with pytest:
Usage Examples
Example: "Investigate File" Prompt in Claude Desktop
Prompt Given
Use the investigate-file prompt to analyze the file at "/Users/username/Desktop/test_hit.txt". Provide the file size, creation and modification times, and SHA-256 hash. Assess if there are any signs of tampering or suspicious characteristics.
Example Response
File Investigation Report
Basic File Information
- File Path: /Users/username/Desktop/test_hit.txt
- File Size: 9 bytes
- Created: June 8, 2025 at 00:26:04.733792 UTC
- Modified: June 8, 2025 at 00:26:04.714230 UTC
- SHA-256 Hash: 9b7729b1ccfe223076659db07b7f0bb888e139907bb8d7019560166176953fcb
Analysis and Assessment
File Characteristics:
- This is a very small file (only 9 bytes), likely containing minimal text content
- The file was created and modified almost simultaneously, with the modification timestamp actually preceding the creation timestamp by about 19 milliseconds - this is unusual but can occur due to filesystem timing precision differences
Temporal Analysis:
- Creation and modification occurred at 00:26:04 UTC
- No specific log entries were found relating to this file’s creation or modification in the system logs
- The logs show normal system activity around that time period, primarily power management and Claude desktop application activity
Security Assessment:
There are no apparent signs of tampering or suspicious characteristics:
- File Size: The 9-byte size is consistent with a small text file
- Timestamps: While the modification time slightly precedes creation time, this is a known filesystem behavior and not indicative of tampering
- Hash Integrity: The SHA-256 hash provides a baseline for future integrity verification
- System Logs: No suspicious file system activity or security events were detected around the creation time
- Location: The file is in a standard user Desktop directory, which is a normal location for user files
Recommendations:
- The file appears to be legitimate with no signs of tampering
- Store the SHA-256 hash for future integrity verification
- Monitor for any unexpected changes by periodically checking its hash
Additional Example Prompts
1. Triage System Logs Prompt
Use the triage-system-logs prompt to search the system logs for the keyword “error”. Summarize the most relevant log entries indicating warnings or security events. Advise if any immediate action is recommended.
2. Correlate Log and File Prompt
Use the correlate-log-and-file prompt to analyze the file “/Users/username/Desktop/test_hit.txt” and search system logs for the keyword “correlation”. Determine if the file modification times align with suspicious log events. Explain the correlation and its forensic implications.
3. Explain Correlation Prompt
Use the explain-correlation prompt with the file “/Users/username/Desktop/test_hit.txt” and keyword “correlation”. Interpret the log hits and file metadata. Provide a concise forensic reasoning summary (under 100 words).
License
MIT License
Acknowledgments
- The Model Context Protocol (MCP) team and community for creating an innovative standard enabling interoperable AI tool integration.
- The FastMCP Python SDK developers for providing a robust and user-friendly framework to build MCP servers.
- The broader open-source and digital forensics communities for inspiring secure and effective AI-driven investigative tooling.
- Projects and initiatives focused on secure AI-agent interfacing and infrastructure automation, which shaped the vision behind this toolkit.
This server cannot be installed
A secure, AI-ready local server that provides digital forensics tools for analyzing logs, verifying file integrity, and generating audit-grade reports.
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