A web scraping API written in Python to fetch data from the Department of Transportation's https://safer.fmcsa.dot.gov

An API to scrape data from the Department of Transportation's Safety and Fitness Electronic Records (SAFER) System.

PHP library wrapper for FMCSA SAFER API

FMCSA QC Mobile API Client

Safer Scraper Streamlit App is a web application that allows users to retrieve company data using the USDOT (United States Department of Transportation) code and fetch their details. The app is built using the Streamlit framework and utilizes Python libraries such as `safer` for accessing the FMCSA SAFER database and `BeautifulSoup` for web scrapin

Plan a truck driver's trip and get the daily log sheets to go with it. Enter where you are, where you're picking up, where you're dropping off, and the hours you've already worked this week. Outbound Spotter maps the route, schedules the required rest and fueling stops, and draws the daily logs the driver has to keep.

Full-stack HOS trip planner for truck drivers with live route mapping, duty-status timeline, 70-hour cycle tracking, fuel/rest stops, and printable FMCSA-style daily logs.

Trip planner for property-carrying truck drivers that auto-generates FMCSA-compliant ELD daily logs and route maps from a single trip input.

Open-source ELD trip planner for commercial drivers. Plan routes, enforce HOS rules, generate log sheets — no SaaS required.

Open-source Agent Skills for DOT / FMCSA compliance. Drop in any AI coding agent (Claude Code, Cursor, Cowork) so it knows trucking regulations like a fleet safety pro.

End-to-end transportation analytics project analyzing FMCSA roadside inspection violations using SQL and Tableau.

Python carrier data extractor for FMCSA SAFER records, legal names, addresses, phone numbers, emails, and logistics prospecting workflows.

About: Daily HOS and DVIR compliance audit tool for Samsara ELD fleets. Flags violations, missing shipping IDs, and drivers approaching the 70-hour weekly limit.

fmCSA carrier data extraction tool

Edge AI computer vision system using Raspberry Pi 5 and Edge Impulse to detect tailgating by CMVs, capture of DOT numbers with automatic reporting to safety departments and eventually to DOT/ FMCSA to affect CSA real-time.

MCP server for DOT/FMCSA compliance reference workflows across trucking regulations, hazardous materials, hours of service, and CSA categories.

Python Selenium scraper for extracting carrier and MC data from FMCSA SAFER, including company details, phone numbers, addresses, and emails.

TruckLog Pro: An FMCSA HOS compliant ELD trip planner built with Django, React, and Leaflet.

Python web scraping toolkit for extracting carrier and logistics data from FMCSA SAFER systems using Selenium and notebook-driven workflows.