Related MCP Server Resources

Explore more AI models, providers, and integration options:

  • Explore AI Models
  • Explore AI Providers
  • Explore MCP Servers
  • LangDB Pricing
  • Documentation
  • AI Industry Blog
  • TMDB MCP Server
  • Surf MCP Server
  • Xano MCP Server
  • Vertex AI MCP Server
  • mcpdemo
Back to MCP Servers
Office Supplies Inventory NANDA Service

Office Supplies Inventory NANDA Service

Public
neeraj-jhawar/my_first_mcp

Provides office supplies inventory data via Model Context Protocol, enabling AI assistants to query item lists and detailed information from a cloud-hosted CSV-based service.

python
0 tools
May 30, 2025
Updated Jun 4, 2025

Supercharge Your AI with Office Supplies Inventory NANDA Service

MCP Server

Unlock the full potential of Office Supplies Inventory NANDA Service through LangDB's AI Gateway. Get enterprise-grade security, analytics, and seamless integration with zero configuration.

Unified API Access
Complete Tracing
Instant Setup
Get Started Now

Free tier available • No credit card required

Instant Setup
99.9% Uptime
10,000+Monthly Requests

Office Supplies Inventory NANDA Service using MCP Server + NANDA Registry + NANDA host client

Create a NANDA service using Model Context Protocol (MCP) server code that provides information about office supplies inventory. This service allows AI assistants to query and retrieve information about office supplies using the MCP standard. You will use cloud hosted server and a web based NANDA host client. No need to install a local server.

You can deploy a consumer facing web-app for any standard inventory using the same framework.

Overview

This project implements a NANDA service using MCP server code that serves office inventory data from a CSV file. It provides tools that allow AI assistants to:

  • Get a list of all available items in the inventory
  • Retrieve detailed information about specific items by name

Prerequisites

  • Python 3.9 or higher
  • Dependencies listed in requirements.txt

Files in this Repository

  • officesupply.py: The main server implementation
  • inventory.csv: CSV file containing the office supply inventory data
  • build.sh: Script for setting up the environment
  • run.sh: Script for running the server
  • requirements.txt: List of Python dependencies

Quick Start

Local Setup

  1. Clone this repository:

    git clone https://github.com/aidecentralized/nanda-servers.git cd office-supplies-shop-server
  2. Choose one of the environment setup options below:

Option A: Using Python venv

  1. Create a Python virtual environment:

    python -m venv venv
  2. Activate the virtual environment:

    • On Linux/macOS:
      source venv/bin/activate
    • On Windows:
      venv\Scripts\activate
  3. Install dependencies:

    pip install -r requirements.txt

Option B: Using Conda

  1. Create a new conda environment:

    conda create --name inventory_env python=3.11
  2. Activate the conda environment:

    conda activate inventory_env
  3. Install dependencies:

    pip install -r requirements.txt

Running the Server Locally to Test

After setting up your environment using either option above:

  1. Run the server:

    python officesupply.py
  2. The server will be available at: http://localhost:8080

Testing with MCP Inspector

  1. Install the MCP Inspector:

    npx @modelcontextprotocol/inspector
  2. Open the URL provided by the inspector in your browser

  3. Connect using SSE transport type

  4. Enter your server URL with /sse at the end (e.g., http://localhost:8080/sse)

  5. Test the available tools:

    • get_items: Lists all item names in the inventory
    • get_item_info: Retrieves details about a specific item

CSV Data Format

The server expects an inventory.csv file with at least the following column:

  • item_name: The name of the inventory item

Additional columns will be included in the item details returned by get_item_info.

Within this purview, you can edit the CSV file for your requirements, and the MCP server should work for your CSV file as well.

Deployment

Preparing for Cloud Deployment

  1. Make sure your repository includes:

    • All code files
    • requirements.txt
    • build.sh and run.sh scripts
  2. Set executable permissions on the shell scripts:

    chmod +x build.sh run.sh

    For Windows, run

    wsl chmod +x build.sh run.sh

Create AWS account

Deploying to AWS AppRunner

  1. Create AWS account

  2. Add your credit card for billing

  3. Go to AWS AppRunner (https://console.aws.amazon.com/apprunner)

  4. Log in (if you’re not already)

  5. Once you're in the App Runner dashboard, you’ll see a blue “Create service” button near the top right of the page. Click that.

  6. Create a new service from your source code repository

  7. Configure the service:

    • Python 3.11 runtime
    • Build command: ./build.sh
    • Run command: ./run.sh
    • Port: 8080
  8. Deploy and wait for completion

  9. Test the public endpoint with MCP Inspector

Registering on NANDA Registry

  1. Go to NANDA Registry
  2. Login or create an account
  3. Click "Register a new server"
  4. Fill in the details:
    • Server name
    • Description
    • Public endpoint URL (without /sse)
    • Tags and categories
  5. Register your server

Usage in NANDA Host, a Browser based Client

  1. Visit nanda.mit.edu
  2. Go to the NANDA host
  3. Add your Anthropic API key
  4. Find your MCP server in the registry
  5. Add it to your host
  6. Test by asking questions that use your server's functionality

Troubleshooting

  • Ensure your CSV file is properly formatted
  • Test the server locally before deploying
  • Verify your public endpoint works with MCP Inspector before registering
  • Check the logs on AWS if deployment fails

Additional Resources

Check out this video tutorial for a walkthrough of setting up and using the MCP server:

Acknowledgments

Based on the NANDA Servers repository. Follow ProjectNanda at https://nanda.mit.edu

Publicly Shared Threads0

Discover shared experiences

Shared threads will appear here, showcasing real-world applications and insights from the community. Check back soon for updates!

Share your threads to help others
Related MCPs5
  • TMDB MCP Server
    TMDB MCP Server

    Provides AI assistants with seamless access to The Movie Database API via Model Context Protocol, en...

    Added May 30, 2025
  • Surf MCP Server
    Surf MCP Server

    Provides tide information by location and date using latitude, longitude, and time zone data via Mod...

    1 tools
    Added May 30, 2025
  • Xano MCP Server
    Xano MCP Server

    Python-based Model Context Protocol server enabling AI assistants to securely interact with Xano ins...

    Added May 30, 2025
  • Vertex AI MCP Server
    Vertex AI MCP Server

    Provides a Model Context Protocol server enabling advanced interaction with Google Cloud's Vertex AI...

    20 tools
    Added May 30, 2025
  • mcpdemo
    mcpdemo

    Provides IP query capabilities using the Model Context Protocol (MCP) to enable efficient and accura...

    Added May 30, 2025