This repository contains an MCP (Model Context Protocol) Server built with FastAPI.
It powers model-based interactions, external API communication, and AI-driven processing.

You can deploy this server in two ways:

• Cloud deployment using Railway
• Local deployment via Claude Desktop

---

Prerequisites

• Python 3.10+
• A Railway account (for cloud deployment)
• Claude Desktop installed (for local MCP deployment)
• requirements.txt dependencies installed

---

Environment Variables

Create a .env file (or set via Railway dashboard):

DYNAMODB_TABLE_NAME=your-dynamo-db-name
S3_BUCKET_NAME=your-s3-bucket-name
AWS_REGION=your-aws-region
AWS_ACCESS_KEY_ID=your-access-key
AWS_SECRET_ACCESS_KEY=your-secret-access-key

For Claude Desktop local deployment, environment variables can be added through the MCP configuration.

---

Deployment Option 1: Railway (Cloud Hosting)

1. Upload or Connect Your Repository

• Push your project to GitHub.
• Go to Railway Dashboard.
• Click “New Project” → “Deploy from GitHub Repo”.
• Select your MCP server repository.

2. Set Environment Variables

In Railway → Settings → Variables, add all keys from your .env.

3. Configure the Start Command

If Railway doesn’t auto-detect it, manually set:

uvicorn app.main:app --host 0.0.0.0 --port $PORT

4. Deploy!

Click Deploy Now, and Railway will build and host your MCP server.

Once live, you’ll get a public URL:

https://your-mcp-server.up.railway.app/

5. Test the Deployment

curl https://your-mcp-server.up.railway.app/

Expected response:

{"message":"Plant Disease MCP API running......."}

---

Deployment Option 2: Claude Desktop (Local MCP)

1. Claude Desktop Setup

• First, make sure you have Claude for Desktop installed. You can install the latest version here.
• If you already have Claude for Desktop, make sure it’s updated to the latest version.
• We’ll need to configure Claude for Desktop for whichever MCP servers you want to use.
• To do this, open your Claude for Desktop App configuration at ~/Library/Application Support/Claude/claude_desktop_config.json in a text editor.
• Make sure to create the file if it doesn’t exist.

macOS/Linux:

code ~/Library/Application\ Support/Claude/claude_desktop_config.json

windows:

code $env:AppData\Claude\claude_desktop_config.json

2. Add MCP Server

You’ll then add your servers in the mcpServers key. The MCP UI elements will only show up in Claude for Desktop if at least one server is properly configured.

macOS/Linux:

{
  "mcpServers": {
    "server-name": {
      "command": "package-installer",     # uv/pip
      "args": [
        "--directory",
        "/ABSOLUTE/PATH/TO/PARENT/FOLDER/mcp-folder",
        "run",
        "server-file.py"
      ]
    }
  }
}

windows:

{
  "mcpServers": {
    "server-name": {
      "command": "package-installer",     #uv/pip
      "args": [
        "--directory",
        "C:\\ABSOLUTE\\PATH\\TO\\PARENT\\FOLDER\\mcp-folder",
        "run",
        "server-file.py"
      ]
    }
  }
}

You may need to put the full path to the uv executable in the command field. You can get this by running which uv / which pip on macOS/Linux or where uv / where pip on Windows.

This tells Claude for Desktop:

1. There’s an MCP server named “server-name”
2. To launch it by running uv --directory /ABSOLUTE/PATH/TO/PARENT/FOLDER/mcp-folder run server-file.py

Save the file, and restart Claude for Desktop.

3. Test with Commands

• Make sure Claude for Desktop is picking up the two tools we’ve exposed in your server-name. You can do this by looking for the Search and tools icon.
• After clicking on the slider icon, you should see all tools listed.
• If your server isn’t being picked up by Claude for Desktop, proceed to the Troubleshooting section for debugging tips.
• If the tool settings icon has shown up, you can now test your server by running the commands in Claude for Desktop.