🚀 Project Overview
MCP-Agentic AI is an intelligent, modular, agent-based system built using the Model Context Protocol (MCP). It demonstrates how AI agents can autonomously:
🚀 connect to external tools
🚀 call MCP server endpoints
🚀 perform reasoning → action loops
🚀 complete complex multi-step workflows
This project is a template to build agentic applications, automate tasks, or integrate AI with backend services.
📚 Features
✔ Agentic AI workflow ✔ Connect to MCP tools / servers ✔ Modular architecture (agents, tools, workflows) ✔ Extendable and developer-friendly ✔ Python-based, simple to run ✔ Great template for production-grade agent systems
🛠️ Tech Stack
✔ Category Tools / Tech
✔ Language Python 3.8+
✔ Protocol Model Context Protocol (MCP)
✔ Agent Framework Custom modular agent system
✔ Package Mgmt pip + venv
✔ Config YAML / JSON
✔ Dev Tools Git, GitHub
✔ Workflows Reasoning → Tool Use → Result
📁 Project Structure
MCP-Agentic AI/
│── agents/ # Core agent logic
│── tools/ # MCP tool integrations
│── workflows/ # Multi-step agent workflows
│── config/ # Config + keys + MCP settings
│── main.py # Entry point
│── requirements.txt
│── README.md
⚙️ Installation
1️⃣ Clone the Repository
git clone https://github.com/VaishnaviSh14/MCP-AGENT.git
cd "MCP Agentic AI"
2️⃣ Create & Activate Virtual Environment
Mac/Linux:
python3 -m venv venv source venv/bin/activate
Windows:
python -m venv venv
venv\Scripts\activate.bat
3️⃣ Install Dependencies
pip install -r requirements.txt
python main.py
🧠 Skills Demonstrated
✔ Agentic AI design patterns
✔ MCP communication & tool invocation
✔ Python modular architecture
✔ Working with external APIs
✔ Workflow automation
✔ Software engineering best practices
✔ GitHub project structure & version control
✔ Environment configuration + secrets mgmt