Inventory Manager

An AI-powered inventory management system built with FastAPI, Model Context Protocol (MCP), and LangChain. A conversational AI agent (powered by Ollama/Llama 3.2) manages items and suppliers in a PostgreSQL database through natural language commands.

Academic project for the Enterprise Application Integration (IS) course — Master's in Computer Engineering, University of Coimbra, 2025/2026.

Features

• Natural Language Interface — manage inventory through a chat UI powered by an LLM agent
• Full CRUD — create, read, update, and delete items and suppliers
• Stock Transfers — transfer quantities between items with validation
• Supplier Management — link items to suppliers, lookup by name
• MCP Server — tools exposed via the Model Context Protocol for AI agent integration
• REST API — standard FastAPI endpoints alongside the AI chat interface

Architecture

Browser (Chat UI)
      │
      │ HTTP
      ▼
  FastAPI Server
      │
      ├── /chat endpoint ──> LangChain Agent (Ollama/Llama 3.2)
      │                            │
      │                      MCP Tools (stdio)
      │                            │
      │                      MCP Server (FastMCP)
      │                            │
      ├── REST endpoints ──────────┤
      │                            │
      ▼                            ▼
  SQLModel / PostgreSQL

The LangChain agent uses a ReAct pattern with MCP tools to interpret user requests, call the appropriate inventory operations, and return natural language responses.

Tech Stack

Component	Technology
Language	Python 3.12
Web Framework	FastAPI + Uvicorn
AI Agent	LangChain + LangGraph
LLM	Ollama (Llama 3.2)
MCP	FastMCP (Model Context Protocol)
ORM	SQLModel
Database	PostgreSQL
Package Manager	uv

Getting Started

Prerequisites

• Python 3.12+
• PostgreSQL
• Ollama with llama3.2 model pulled
• uv package manager

Setup

# Install dependencies
uv sync

# Configure database connection
# Create a .env file with:
DATABASE_URL="postgresql://postgres:[email protected]:5432/mcp_is_project"

# Run the server
uv run python main.py

The app will be available at:

• Chat UI: http://localhost:8000/ui
• REST API: http://localhost:8000/docs

Project Structure

MCP-IS-PROJECT/
├── main.py            # FastAPI app with REST endpoints and chat
├── mcp_server.py      # MCP server with all inventory tools
├── agent.py           # LangChain ReAct agent with Ollama
├── models.py          # SQLModel data models (Item, Supplier)
├── services.py        # Business logic layer
├── database.py        # Database connection and setup
├── static/            # Chat UI frontend
├── db_model.txt       # Database schema documentation
└── pyproject.toml     # Dependencies and project config

Team

• Francisco Pereira
• Tiago Mendes

License

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