💸 FinancialAssistant

Name: 💸 FinancialAssistant
Author: nielsenfonseca

@nielsenfonseca

リポジトリ

💸 FinancialAssistant について

Financial MultiAgent Colaboration with MCP Server with Tools

#financial-assistant #financial-tools #investment-advisor

基本情報

カテゴリ

その他

ランタイム

python

トランスポート

stdio

公開者

nielsenfonseca

設定

以下の設定を使って、このサーバーを MCP 対応クライアントに追加してください。

{
  "mcpServers": {
    "FinancialAssistant": {
      "command": "python",
      "args": [
        "-m",
        "venv",
        "venv"
      ]
    }
  }
}

ツール

ツールは検出されませんでした

ツールは README から自動的に抽出されます。メンテナーは ## Tools という見出しの下に記載することで、このタブに反映できます。

概要

What is FinancialAssistant?

FinancialAssistant is a smart financial assistant that uses LLMs and a modular agent-based architecture to help users calculate emergency funds, evaluate savings capacity, get investment suggestions, and discuss financial education. It integrates external APIs for financial calculations and uses the LLM to explain results in a clear, empathetic, and personalized way.

How to use FinancialAssistant?

Clone the repository, create a Python 3.10+ virtual environment, install dependencies with pip install -r requirements.txt, set the GOOGLE_API_KEY and MCP_SERVER_URL in a .env file, then run python main.py to start the assistant.

Key features of FinancialAssistant

Four specialized agents: Generic, Emergency Fund, Savings, and Investment.
LLM-powered router detects user intent and directs to the correct agent.
Conversational graph (LangGraph) maintains multi‑turn dialogue.
External API tools calculate monthly expenses, ideal reserve, savings capacity, and investment suggestions.
Google Gemini used as the underlying LLM (via langchain_google_genai).
Empathetic, human‑friendly explanation of all financial calculations.

Use cases of FinancialAssistant

Calculating the ideal size of an emergency fund based on monthly expenses.
Analyzing monthly spending to determine how much a user can save.
Getting personalized investment suggestions aligned with the user’s financial profile.
Learning the basics of personal finance through natural conversation.

FAQ from FinancialAssistant

What programming language and dependencies does FinancialAssistant require?

It requires Python 3.10 or higher and uses LangGraph, LangChain, Google Gemini (via langchain_google_genai), the Requests library, and python‑dotenv. All dependencies are listed in requirements.txt.

How do I configure FinancialAssistant to run?

You must create a .env file with GOOGLE_API_KEY (for Gemini) and MCP_SERVER_URL. The assistant expects a running MCP server at the given URL to perform financial calculations.

Does FinancialAssistant store my financial data?

The README does not mention data storage or privacy practices. It only describes that external APIs perform calculations; no local persistence is detailed.

What LLM does FinancialAssistant use?

It uses Google Gemini through the langchain_google_genai integration.

Is FinancialAssistant a standalone app or an MCP server?

FinancialAssistant is a conversational agent that you run locally. It depends on an external MCP server (via MCP_SERVER_URL) to handle the financial calculation tools.