What is the MCP Firmware Log Analysis Server?

The MCP Firmware Log Analysis Server is an AI-powered tool designed to help firmware developers quickly identify, analyze, and resolve critical issues in embedded systems through automated log parsing and expert-level analysis.

How does the AI work in MCP Server?

MCP Server uses GPT-4 integration to provide expert-level firmware debugging insights, root cause analysis, actionable recommendations, and confidence scoring for identified issues.

What log formats does MCP Server support?

MCP Server supports .log, .txt, and .json log files.

What types of issues can MCP Server detect?

MCP Server can detect various issues, including hard faults, watchdog resets, sensor failures, assertions, panics, stack overflows, memory corruption, boot failures, hardware faults, and sensor issues.

What kind of reports does MCP Server generate?

MCP Server generates HTML reports, JSON API responses, and Markdown exports.

How do I install MCP Server?

First, clone the repository, then install the dependencies using pip install -r requirements.txt. Next, configure your OpenAI API key in a .env file. Finally, start the server using python run_server.py.

What are the prerequisites for using MCP Server?

You need Python 3.8+, an OpenAI API key, and optionally, the addr2line tool for ELF symbol resolution.

How do I access the web interface?

Navigate to http://localhost:8000 in your web browser after starting the server.

Can I use MCP Server programmatically?

Yes, MCP Server provides a REST API that allows for programmatic integration. Example: curl -X POST "http://localhost:8000/analyze-log" -F "log_file=@firmware_crash.log"

What environment variables can I configure?

You can configure OPENAI_API_KEY, OPENAI_MODEL, OPENAI_MAX_TOKENS, OPENAI_TEMPERATURE, HOST, PORT, DEBUG, MAX_LOG_LINES, and CONFIDENCE_THRESHOLD.

What are the file limits for log analysis?

The maximum file size is 50MB, supported extensions are .log, .txt, .json, .elf, .bin, and the max log lines is 10,000 (configurable).