MCP 101 Tutorial: Build Your Own Modular AI Agent for Stock Investment Insights

Author(s): Lorentz Yeung

Originally published on Towards AI.

MCP 101 Tutorial: Build Your Own Modular AI Agent for Stock Investment Insights

Welcome to this MCP 101 tutorial! A brief context of the project I started building AI systems for stock investment in 2021 with a sentiment analysis-based trading system powered by XGBoost.

This article details the author’s journey in developing a modular AI system for stock investment, beginning with a sentiment analysis trading system and transitioning into a more robust framework utilizing the Multi-Component Protocol (MCP). The tutorial provides concrete steps for setting up an AI agent, installing necessary dependencies, and integrating multiple servers to facilitate real-time stock queries and mathematical operations, culminating in advice on extending the system with additional features like sentiment analysis and prediction models.

Read the full blog for free on Medium.

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Published via Towards AI