FinGPT-Powered Agents Framework: Financial Agents via MCP

Welcome to the documentation for the FinGPT-Powered Agents Framework, a modular architecture designed to facilitate the creation of sophisticated financial agents through the use of the Model Context Protocol (MCP).

Documentation Contents:

• Overview

About FinGPT-Powered Agents

The FinGPT-Powered Agents Framework leverages Large Language Models (LLMs), modular components of the MCP protocol, and the MCP protocol itself to enable flexible, powerful, and transparent financial agents. This framework allows developers to integrate real-time market data, user-specific portfolios, remote analytics services, and advanced computational tools seamlessly into financial agents.

Key Features

• Model Context Protocol (MCP): Standardized interactions between LLMs, tools, and data.

• Flexible Architecture: Easily integrate and swap modular components.

• Real-Time Financial Data: Integration with remote services such as market APIs, brokerage accounts, analytical tools, etc.

• Personalized Financial Agents: Customizable financial agents tailored to individual profiles, preferences, and tasks.

Buffett-Agent as an Example

An agent tasked as a financial advisor, the Buffett-Agent will use the following framework:

Buffett-Agent Documentation:

• Introduction
  • Background
  • Why Warren Buffett?
  • Project Objectives
  • Research Questions
• Methodology
  • Research Design
  • Data Collection
  • LoRA Implementation
  • Training Process
  • Evaluation Framework
• Dataset
  • Source Materials
  • Data Processing
  • Structured Format
• Model
• Experiment
  • Example: Defending Capitalism

Getting Started

Add Later

License

This project is licensed under the MIT License – see the LICENSE file for details.