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A containerized MCP server for parsing OT/ICS packet captures, specifically supporting Modbus and BACnet protocols via tshark. It provides structured JSON outpu
A containerized MCP server for parsing OT/ICS packet captures, specifically supporting Modbus and BACnet protocols via tshark. It provides structured JSON output from PCAP files to enable LLMs to analyze industrial network traffic and derive device inventories.
A containerized MCP server that parses OT/ICS packet captures and returns structured JSON. Designed to plug into a Claude Code workflow for analyzing saved PCAP files from Modbus/TCP and BACnet/IP networks.
Status: [EXPERIMENTAL]
otparse exposes two MCP tools:
parse_modbus_pcap -- reads a saved PCAP file, extracts Modbus/TCP transactions using tshark, and returns decoded frames plus a basic device inventory derived from observed IPs.parse_bacnet_pcap -- reads a saved PCAP file, extracts BACnet/IP packets using tshark, and returns decoded frames plus a basic device inventory derived from observed IPs.Both tools accept a path to a PCAP inside the container and an optional packet limit. Output is structured JSON that an LLM can reason over directly.
This grew out of interest in OT/ICS security and the gap between "I have a PCAP from an industrial network" and "I can actually understand what devices were talking to each other and whether anything looks off." Wrapping tshark in an MCP server means Claude can do the first layer of that analysis without a separate toolchain.
The container design follows the same pattern as netparse: read-only evidence mount, no outbound network access, non-root user.
docker build -t otparse-mcp .
python3 -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt
pip install -e .
tshark must be available in your PATH for local development.
docker run --rm -i \
--network none \
-v /srv/evidence:/evidence:ro \
otparse-mcp:latest
{
"mcpServers": {
"otparse": {
"command": "docker",
"args": [
"run", "--rm", "-i",
"--network", "none",
"-v", "/srv/evidence:/evidence:ro",
"otparse-mcp:latest"
]
}
}
}
Once connected, ask Claude something like:
"Parse the Modbus capture at
/evidence/modbus/example.pcapand summarize what devices were communicating."
Claude will call parse_modbus_pcap and work from the returned JSON.
python -m otparse.server
otparse/
├── otparse/
│ ├── __init__.py
│ ├── server.py # FastMCP server, tool definitions
│ ├── models.py # Pydantic models for all inputs/outputs
│ ├── parsers/
│ │ ├── common.py # Shared helpers (path validation, tshark check, type coercion)
│ │ ├── modbus.py # Modbus/TCP parser using pyshark + tshark
│ │ └── bacnet.py # BACnet/IP parser using pyshark + tshark
│ └── analyzers/
│ └── devices.py # Builds device inventory from parsed transactions
├── Dockerfile
├── docker-compose.yml
├── pyproject.toml
├── requirements.txt
└── README.md
See docs/tool-reference.md for full parameter and output documentation.
direction (request vs. response) detection depends on pyshark exposing the right attributes. Some captures may produce "unknown" for most frames.null on older tshark builds.docker-compose.yml is included for convenience but assumes the repo root layout matches the build context. Adjust build: paths if your layout differs.packet_limit parameter (default: 500) that caps the number of matching packets decoded per run. This limit is in place during early testing and will be removed in a future version. For large captures, increase the limit explicitly when calling the tool.Sample ICS PCAPs suitable for testing can be found in the ITI ICS-Security-Tools repository, which maintains a collection of ICS protocol captures for security research.
extract_ics_devices tool combining Modbus and BACnet inventory into a single viewSee CHANGELOG.md
Добавь это в claude_desktop_config.json и перезапусти Claude Desktop.
{
"mcpServers": {
"otparse-mcp": {
"command": "npx",
"args": []
}
}
}