Analysis updated 2026-05-18
Log daily expenses and tag each one as a need or a want to spot spending habits.
View spending trends with a day-by-day area chart and a category pie chart.
Check a budget health indicator to see if you're on track, close, or over budget.
Let an AI model automatically suggest a category when adding a new expense.
| nikithadineshkumar/financetracker | forgetmeai/freedeepseekapi | mattpocock/boilersuit | |
|---|---|---|---|
| Stars | 31 | 31 | 31 |
| Language | JavaScript | JavaScript | JavaScript |
| Last pushed | — | — | 2018-10-26 |
| Maintenance | — | — | Dormant |
| Setup difficulty | moderate | moderate | moderate |
| Complexity | 3/5 | 3/5 | 3/5 |
| Audience | general | general | developer |
Figures from each repo's GitHub metadata at analysis time.
Requires setting up MongoDB and a Gemini API key for the AI categorizer feature.
FinanceTracker is a personal finance web application for recording daily expenses, managing a monthly budget, and reviewing spending patterns over time. Users create an account, log in securely, and can then add, edit, or delete expense entries. Each entry can be assigned to one of sixteen preset categories such as Food, Transport, Shopping, or Medicine, and tagged as either a need or a want to help identify spending habits. Custom categories are also supported. The main dashboard presents spending data as charts: a day-by-day area graph for tracking trends and a pie chart broken down by category. A budget health indicator shows at a glance whether current spending is comfortable, approaching the limit, or over it, using green, yellow, and red status colors. Past months of expenses can be browsed through a history view, and category-by-category monthly summaries are available. One notable feature is an AI expense categorizer powered by Google's Gemini 2.0 model. When adding an expense, the AI can automatically suggest which category it belongs to based on the description. A budget advisor chatbot and smart spending insights are listed on the roadmap but are not yet built. On the technical side, user accounts use JSON Web Token authentication and password hashing. The application is split into a React frontend and a Node.js and Express backend connected to a MongoDB database. The project is built and maintained by a single developer, is released under the MIT license, and is described as currently in active development. A live demo is noted as coming after deployment to Vercel and Render.
A personal finance web app for tracking expenses, budgets, and spending trends, with an AI assistant that suggests expense categories.
Mainly JavaScript. The stack also includes React, Node.js, Express.
Setup difficulty is rated moderate, with roughly 1h+ to a first successful run.
Mainly general.
This repo across BitVibe Labs
Verify against the repo before relying on details.