Sustainable Spending Dashboard MCP Server

@Rohit8y

代码仓库

基本信息

分类

其他

许可证

MIT license

传输方式

stdio

作者

Rohit8y

关于 Sustainable Spending Dashboard MCP Server

AI Agents to support sustainable spending on Bunq using MCP servers

#sustainable-spending#ai-dashboard#climate-action

Sustainable Spending Dashboard MCP Server 配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

{
  "mcpServers": {
    "bunq-hackathon-agents-6.0": {
      "command": "python",
      "args": [
        "-m",
        "venv",
        "venv"
      ]
    }
  }
}

Sustainable Spending Dashboard MCP Server 工具

工具列表暂未提供

当前收录暂时没有可展示的工具列表，不代表服务没有工具。请查阅项目文档了解支持的能力。

工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。

概览

What is 🌍 Sustainable Spending Dashboard?

A financial analytics tool that connects your spending data to climate impact. It uses LLMs to classify transactions, calculate carbon footprint, and enable automated carbon offset transfers via Bunq. Built for individuals who want to understand and reduce their environmental impact through everyday spending.

How to use 🌍 Sustainable Spending Dashboard?

Clone the repository, create a Python virtual environment, install dependencies from requirements.txt, and add a Bunq API key to a .env file. Then run streamlit run dashboard.py to launch the interactive dashboard.

Key features of 🌍 Sustainable Spending Dashboard

Classify spending into intuitive categories.
Calculate total CO₂ emissions and CO₂ per € spent.
Assign a sustainability zone (Green / Yellow / Red).
Visualize insights in a modern dashboard.
Transfer offset amounts to a Bunq green account.
Display motivational messages like “you planted 3 trees!”
Show a gamified leaderboard comparing offset-to-spend ratios.

Use cases of 🌍 Sustainable Spending Dashboard

Understand your personal carbon footprint from monthly expenses.
Automate small offset transfers to a Bunq green account.
Compete with peers on a sustainability leaderboard.
Track progress toward more eco-friendly spending habits.

常见问题

What data does it use?

It can analyze a sample `transactions.csv` file or connect to real Bunq accounts via the Bunq API key stored in `.env`.

What are the runtime requirements?

Python 3 with Streamlit, `pydantic_ai`, Gemini/OpenAI LLM access, Pandas, Matplotlib, and the Bunq SDK. All are listed in `requirements.txt`.

How is the sustainability zone determined?

Green (CO₂ per € < 0.4), Yellow (0.4–0.6), Red (> 0.6). The zone is displayed as a dynamic badge in the app.

Can I use it without a Bunq account?

Offset transfers require a Bunq account and API key. Other features (classification, CO₂ calculation, visualization) work with the sample data.

What LLMs are supported?

The dashboard uses Gemini and OpenAI via the `pydantic_ai` agent orchestration library for spending classification and CO₂ reasoning.

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