MCP Inventory Manager
Manages items and suppliers in a PostgreSQL database, providing CRUD operations, stock transfers, and supplier management through natural language commands.
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@MCP Inventory ManagerShow me all items with stock below 10"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
MCP 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
Related MCP server: Stock MCP
Architecture
Browser (Chat UI)
│
│ HTTP
▼
FastAPI Server
│
├── /chat endpoint ──> LangChain Agent (Ollama/Llama 3.2)
│ │
│ MCP Tools (stdio)
│ │
│ MCP Server (FastMCP)
│ │
├── REST endpoints ──────────┤
│ │
▼ ▼
SQLModel / PostgreSQLThe 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
Setup
# Install dependencies
uv sync
# Configure database connection
# Create a .env file with:
DATABASE_URL="postgresql://postgres:postgres@127.0.0.1:5432/mcp_is_project"
# Run the server
uv run python main.pyThe app will be available at:
Chat UI:
http://localhost:8000/uiREST 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 configTeam
Francisco Pereira
Tiago Mendes
License
This project is licensed under the MIT License — see the LICENSE file for details.
This server cannot be deployed
Maintenance
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