ltchiptool-mcp
Enables chip-level firmware extraction and analysis for BK7231 family IoT devices via UART, supporting flash dumping, decryption, and partition extraction.
README
ltchiptool-mcp
MCP server wrapping ltchiptool and bk7231tools for chip-level firmware extraction. Drives the BK7231 family (Tuya/IoT plugs) over UART, dumps full flash, decrypts and extracts partitions. Exposes operations as Model Context Protocol tools over stdio transport.
Built for use with Claude Code on a Raspberry Pi 5, but works with any MCP client and any USB-UART substrate.
What it does
- Chip info: detect chip type, bootloader, MAC, flash size, and per-chip encryption key
- Flash dump: full encrypted flash read via UART (yank-restore HITL for the connect window)
- Partition extraction: decrypt + dissect into bootloader / app / storage JSON
- Discovery: look up boards in ltchiptool's catalog (CB3S, WB3S, CUCO-Z1-N, etc.) to map module silkscreen to chip family
- Substrate-agnostic: any USB-UART path works (FT232, BP6 bridge mode, etc.). External 3.3V supply recommended for BK7231 (BP6 onboard PSU trips on inrush).
Requirements
- Python 3.11+
- User in
dialoutgroup for serial access (sudo usermod -aG dialout $USER) - A USB-UART dongle (FT232 or similar) and an external 3.3V supply (lab PSU, regulated buck, or Pi GPIO header pin 1)
Install
git clone https://github.com/mplogas/ltchiptool-mcp.git
cd ltchiptool-mcp
pip install -e ".[dev]"
bk7231tools is a transitive dependency of ltchiptool, no separate install needed.
MCP Client Configuration
Add to your .mcp.json:
{
"mcpServers": {
"ltchiptool": {
"command": "/path/to/.venv/bin/python",
"args": ["-m", "ltchiptool_mcp"],
"env": {
"PIDEV_ENGAGEMENTS_DIR": "/path/to/engagements"
}
}
}
}
PIDEV_ENGAGEMENTS_DIR controls where standalone-engagement output is written. Defaults to ./engagements/ relative to the package root.
Tools
| Tool | Safety Tier | Description |
|---|---|---|
prepare_chip_info |
read-only | Operator instructions for yank-restore. No subprocess. |
start_chip_info |
allowed-write | Run ltchiptool flash info. Returns chip info dict (type, MAC, encryption key, flash size). |
prepare_flash_read |
read-only | Validate args, resolve output path, return operator instructions. |
start_flash_read |
allowed-write | Run ltchiptool flash read. Long-running (~3-5 min for 2 MiB). |
dissect_dump |
allowed-write | Run family's dissect command. Decrypts + extracts partitions. |
list_supported_families |
read-only | Strategy registry of validated families. |
list_boards |
read-only | All boards ltchiptool knows about, each with vendor/product/family. |
prepare/start protocol
prepare_* and start_* tools come in pairs and are stateless. The natural agent flow:
- Agent calls
prepare_chip_info(serial_port, family)-- gets operator instructions - Agent relays instructions to operator, waits for "ready"
- Agent calls
start_chip_info(serial_port, family)with the same args -- runs ltchiptool
If the HITL window is missed, start_* returns {"error": "hitl_window_missed", ...} and the agent re-invokes start_* (no need to re-prepare). prepare and start are independently callable; calling start without prepare just skips the operator briefing.
Safety Model
Three tiers enforced at the MCP server boundary:
- read-only: full autonomy, no side effects
- allowed-write: autonomous execution, all calls logged
- approval-write: reserved for future
flash writewrapper (no MVP tools)
ltchiptool's flash read and flash info cannot brick the chip -- they are read-only operations from the chip's perspective. The HITL primitive is timing, not safety.
Architecture
mitm-mcp client (Claude Code, etc.)
|
stdio transport
|
ltchiptool-mcp (server.py)
|
tools.py -> runner.py -> subprocess.run("ltchiptool ...")
-> subprocess.run("bk7231tools ...")
|
USB serial (UART) -> Target chip
runner.py is the only module that calls subprocess. Everything else routes through it. parsers.py handles text-to-dict for ltchiptool's table output and bk7231tools' container/storage output. families.py holds the per-family strategy registry.
Family scope
MVP: BK7231N + BK7231T (Tuya/IoT plug ecosystem, share the same yank-restore procedure).
The architecture supports any ltchiptool family. New families register a FamilyStrategy in families.py with their own ltchiptool_arg, HITL action description, dissect command, and parsers. We do not promise families work until we have target hardware to validate.
Tests
pytest # all unit tests
pytest -m hardware # integration, requires real BK7231 target
The hardware tests are gated by pytest.mark.hardware and skipped by default.
Why a separate MCP from buspirate-mcp
ESP-class workflows depend on the BP6's bridge mode + esptool, so they live in buspirate-mcp. BK7231-class workflows do not -- the BP6 onboard PSU trips on Beken inrush, so external power is required, and the substrate is whatever USB-UART works. Decoupling the chip-family extraction from the BP6 substrate keeps both submodules focused.
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.