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 "Install 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: Odoo MCP Server
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 installed
Maintenance
Resources
Unclaimed servers have limited discoverability.
Looking for Admin?
If you are the server author, to access and configure the admin panel.
Latest Blog Posts
MCP directory API
We provide all the information about MCP servers via our MCP API.
curl -X GET 'https://glama.ai/api/mcp/v1/servers/FranciscoPereira474/MCP-Server'
If you have feedback or need assistance with the MCP directory API, please join our Discord server