Forensics MCP Server

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.

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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

  • šŸ” 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.
  • šŸ›”ļø Air-Gapped & Offline Ready: Built-in offline threat intelligence database with known sample signatures (EICAR, WannaCry, Mimikatz) for secure, zero-data-leakage incident response.
  • šŸ“‹ 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).

šŸš€ 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

šŸ”Œ 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


šŸ› ļø 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

šŸ“‚ Project Architecture

forensics-mcp-framework/
ā”œā”€ā”€ pyproject.toml
ā”œā”€ā”€ .env.example
ā”œā”€ā”€ README.md
ā”œā”€ā”€ evidence/                  # Evidence locker & chain of custody ledger
│   ā”œā”€ā”€ suspect_photo.jpg
│   ā”œā”€ā”€ eicar_test.com
│   └── chain_of_custody.jsonl
└── src/
    ā”œā”€ā”€ server.py              # Master FastMCP bootstrap & dynamic assembler
    ā”œā”€ā”€ core/
    │   ā”œā”€ā”€ discovery.py       # Host & container capability scanner
    │   ā”œā”€ā”€ custody.py         # Tamper-evident append-only chain of custody
    │   └── health.py          # System diagnostics & health reporter
    ā”œā”€ā”€ tools/
    │   ā”œā”€ā”€ metadata.py        # ExifTool & MIME mismatch detector
    │   ā”œā”€ā”€ strings_ioc.py     # String & IOC scanner (IP, URL, Base64, shell)
    │   ā”œā”€ā”€ threat_intel.py    # Offline/online threat intelligence
    │   ā”œā”€ā”€ memory_vol.py      # Volatility 3 memory analysis engine
    │   └── dynamic_cli.py     # CLI wrappers (binwalk, tshark, objdump, gdb)
    ā”œā”€ā”€ resources/
    │   └── system_resources.py# MCP Resources
    └── prompts/
        └── triage_prompts.py  # Structured DFIR workflows

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