Forensics MCP Server
Enables AI agents to perform digital forensics and incident response tasks by dynamically discovering and utilizing host tools for memory analysis, metadata extraction, threat detection, and file dissection.
README
Self-Assembling Forensic MCP Server (FastMCP / Python)
A modular Digital Forensics and Incident Response (DFIR) Model Context Protocol (MCP) server built with Python and FastMCP (mcp>=2.0.0).
It dynamically discovers host & container forensic utilities at startup and automatically self-assembles functional tools, resources, and triage prompts for local LLMs and AI agents (Ollama, Claude, Cursor, Antigravity, etc.).
🌟 Features
- 🔍 Dynamic Capability Discovery: Probes host environment paths, installed binaries (
exiftool,strings,volatility3,binwalk,tshark,objdump,gdb,yara), and Docker runtimes. Missing tools are gracefully reported without crashing. - 🧩 Self-Assembling Tool Primitives: Automatically registers only the tools available in the host environment.
- 🛡️ Air-Gapped & Offline Ready: Built-in offline threat intelligence database with known sample signatures (EICAR, WannaCry, Mimikatz) for secure, zero-data-leakage incident response.
- 📋 Tamper-Evident Chain of Custody: Every tool execution, inspected artifact, SHA-256 checksum, and action parameter is cryptographically hashed and logged to an append-only ledger (
evidence/chain_of_custody.jsonl). - 🩺 Self-Reporting Health & Resources: Real-time capability matrix (
forensics://capabilities), custody logs (forensics://custody), and system health (forensics://health). - ⚡ Dual Transport: Supports standard STDIO for native MCP clients (Cursor, Claude, Antigravity) and SSE/HTTP for web LLM agents (Ollama, Open WebUI).
🚀 Quick Start
1. Prerequisites
- Python 3.10+ (or uv)
2. Run the Server
Option A: Native STDIO Transport (For Local Agents / Cursor / Claude)
cd /home/b47m4n/Projects/forensics-mcp-framework
uv run src/server.py
Option B: SSE / HTTP Transport (For Web / Remote LLMs)
cd /home/b47m4n/Projects/forensics-mcp-framework
uv run src/server.py --transport sse --port 8000
🔌 Connecting to Local LLMs & Agents
1. Antigravity / Claude / Cursor (claude_desktop_config.json / mcp.json)
{
"mcpServers": {
"forensic-analyzer": {
"command": "uv",
"args": [
"--directory",
"/home/b47m4n/Projects/forensics-mcp-framework",
"run",
"src/server.py"
]
}
}
}
2. Local LLM via Ollama + MCP
Connect your local model (e.g. llama3.1, qwen2.5-coder) via SSE endpoint:
http://localhost:8000/sse
🛠️ Discovered Tool Catalog
| Tool | Category | Dynamic Condition | Description |
|---|---|---|---|
extract_metadata |
Metadata & Files | Always Available | Computes hashes (MD5/SHA256), EXIF tags, and detects MIME mismatches |
extract_strings |
Static Analysis | Always Available | Extracts printable ASCII & Unicode strings |
scan_iocs |
Threat Detection | Always Available | Scans for C2 URLs, IP addresses, Base64 blobs, command execution |
check_threat_intel |
Threat Intel | Always Available | Checks hashes against offline signatures and optional live APIs |
system_health_check |
Diagnostics | Always Available | Health status, storage check, and tool readiness |
windows_image_info |
Memory Forensics | vol or Docker |
Volatility 3 windows.info |
windows_pslist |
Memory Forensics | vol or Docker |
Volatility 3 windows.pslist |
windows_pstree |
Memory Forensics | vol or Docker |
Volatility 3 windows.pstree |
windows_netscan |
Memory Forensics | vol or Docker |
Volatility 3 windows.netscan |
windows_malfind |
Memory Forensics | vol or Docker |
Volatility 3 windows.malfind (injected code) |
binwalk_scan |
File Carving | binwalk present |
Firmware signature and filesystem carving |
pcap_analyze |
Network Forensics | tshark present |
Dissects PCAP network packet captures |
binary_disassemble |
Reverse Eng | objdump present |
Disassembles binary machine instructions |
gdb_inspect |
Debugging | gdb present |
Automated batch debugging inspection |
yara_scan |
Signature Match | yara present |
Scans evidence against YARA rule files |
📂 Project Architecture
forensics-mcp-framework/
├── pyproject.toml
├── .env.example
├── README.md
├── evidence/ # Evidence locker & chain of custody ledger
│ ├── suspect_photo.jpg
│ ├── eicar_test.com
│ └── chain_of_custody.jsonl
└── src/
├── server.py # Master FastMCP bootstrap & dynamic assembler
├── core/
│ ├── discovery.py # Host & container capability scanner
│ ├── custody.py # Tamper-evident append-only chain of custody
│ └── health.py # System diagnostics & health reporter
├── tools/
│ ├── metadata.py # ExifTool & MIME mismatch detector
│ ├── strings_ioc.py # String & IOC scanner (IP, URL, Base64, shell)
│ ├── threat_intel.py # Offline/online threat intelligence
│ ├── memory_vol.py # Volatility 3 memory analysis engine
│ └── dynamic_cli.py # CLI wrappers (binwalk, tshark, objdump, gdb)
├── resources/
│ └── system_resources.py# MCP Resources
└── prompts/
└── triage_prompts.py # Structured DFIR workflows
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