Ansys_Workbench_Scripting_MCP

cth1975/Ansys_Workbench_Scripting_MCP

3.1

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A beginner-friendly Model Context Protocol (MCP) server that demonstrates how to create and expose text resources and prompt templates.

Simple FastMCP Server

A beginner-friendly Model Context Protocol (MCP) server that demonstrates how to create and expose text resources and prompt templates. This is perfect for learning MCP fundamentals!

What is MCP?

Model Context Protocol (MCP) is a standardized way for AI assistants (like Claude) to access external resources and tools. Think of it as a bridge between AI models and your custom data or functionality.

What This Server Does

This simple server exposes two types of MCP capabilities:

1. Text Resources 📄

Static content that can be retrieved by AI assistants:

  • Company Information: Basic company details
  • Product Catalog: List of products and pricing
  • API Documentation: REST API docs and guidelines

2. Prompt Templates 🎯

Reusable prompt templates that accept parameters:

  • analyze_data: Generate data analysis prompts
  • write_email: Create professional email templates
  • code_review: Generate code review checklists

Quick Start

Option 1: Super Easy Launch 🚀 (Recommended for Beginners)

Use our automated launcher that starts everything for you:

# This will automatically start both the MCP server and MCP Inspector
python launcher.py

The launcher will:

  • ✅ Check and install dependencies automatically
  • 🚀 Start your MCP server in the background
  • 🌐 Launch MCP Inspector in your browser
  • 🔗 Show you exactly how to connect them
  • 🧹 Clean up everything when you press Ctrl+C

That's it! The launcher handles everything automatically and gives you clear instructions.

Option 2: Manual Setup

If you prefer to understand each step or want more control:

1. Install Dependencies

First, make sure you have Python 3.8+ and Node.js installed, then:

# Create a virtual environment (recommended)
python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

# Install dependencies
pip install -r requirements.txt
2. Test the Server

Run the server directly to make sure it starts without errors:

python server.py

The server will start and wait for MCP protocol messages. You should see it running (it won't print anything - that's normal!). Press Ctrl+C to stop it.

Testing with MCP Inspector

MCP Inspector is a web-based tool for testing MCP servers.

If Using the Launcher 🚀

If you used python launcher.py, everything is already set up! Just follow the connection instructions shown in your terminal.

Manual MCP Inspector Setup

If you're doing manual setup, here's how to connect MCP Inspector to your server:

1. Install MCP Inspector
# Install globally via npm
npm install -g @modelcontextprotocol/inspector

# Or run directly with npx (no installation needed)
npx @modelcontextprotocol/inspector
2. Start the Inspector
# If installed globally:
mcp-inspector

# Or with npx:
npx @modelcontextprotocol/inspector

This will open a web browser with the MCP Inspector interface.

3. Connect to Your Server

Current Running Setup (Copy & Paste Ready):

🌐 MCP Inspector URL: http://localhost:6274/?MCP_PROXY_AUTH_TOKEN=3c4c9d201c44466984c7bb6950fa75ee1974b9c3576d2a533460dff2e736798a

In the MCP Inspector interface:

  1. Transport Type: Select "stdio"

  2. Command:

    /Users/christopherhoughton/Dropbox/Code/Ansys_Workbench_Scripting_MCP/.venv/bin/python

  3. Args:

    /Users/christopherhoughton/Dropbox/Code/Ansys_Workbench_Scripting_MCP/server.py

  4. Working Directory:

    /Users/christopherhoughton/Dropbox/Code/Ansys_Workbench_Scripting_MCP

  5. Click "Connect"

Generic Setup (for other users):

In the MCP Inspector interface:

  1. Transport Type: Select "stdio" (this is how our server communicates)

  2. Command: Enter the full path to your server:

    python /full/path/to/your/server.py

    For example:

    python /Users/yourname/simple-mcp-server/server.py

  3. Working Directory: Set to your project directory:

    /Users/yourname/simple-mcp-server

  4. Click "Connect"

4. Explore the Server

Once connected, you can:

Test Resources:
  1. Go to the "Resources" tab
  2. You'll see three resources listed:
    • text://company_info
    • text://product_catalog
    • text://api_docs
  3. Click on any resource to view its content
Test Prompts:
  1. Go to the "Prompts" tab
  2. You'll see three prompts:
    • analyze_data
    • write_email
    • code_review
  3. Select a prompt and fill in the parameters
  4. Click "Get Prompt" to see the generated prompt text

Understanding the Code

Server Structure

# 1. Import MCP libraries
from mcp.server import Server
from mcp.server.stdio import stdio_server

# 2. Create server instance
server = Server("simple-fastmcp-server")

# 3. Define handlers with decorators
@server.list_resources()
@server.read_resource()
@server.list_prompts()
@server.get_prompt()

# 4. Run the server
asyncio.run(main())

Key Concepts

  • Resources: Static content identified by URIs (like text://company_info)
  • Prompts: Template functions that accept parameters and return customized prompts
  • Handlers: Functions decorated with @server.decorator() that respond to MCP requests
  • stdio Transport: Communication method using standard input/output streams

Adding Your Own Content

Add a New Resource:

  1. Add data to the SAMPLE_DATA dictionary:

    SAMPLE_DATA["my_resource"] = "My custom content here"

  2. Add to the list_resources() function:

    Resource(
    uri="text://my_resource",
    name="My Resource",
    description="Description of my resource",
    mimeType="text/plain"
)
Add a New Prompt:

  1. Add to list_prompts():

    Prompt(
    name="my_prompt",
    description="What my prompt does",
    arguments=[
        PromptArgument(
            name="parameter_name",
            description="What this parameter is for",
            required=True
        )
    ]
)

  2. Add handling in get_prompt():

    elif name == "my_prompt":
    param = arguments.get("parameter_name", "default_value")
    prompt_text = f"Custom prompt using {param}"

Troubleshooting

Common Issues:

  1. "Command not found" in MCP Inspector

    • Make sure you're using the full absolute path to your server.py file
    • Ensure Python is in your PATH

  2. "Connection failed"

    • Check that your server runs without errors when started directly
    • Verify all dependencies are installed

  3. "Module not found" errors

    • Make sure you've activated your virtual environment
    • Run pip install -r requirements.txt again

Debug Mode

To see what's happening, you can add some logging to your server:

import logging
logging.basicConfig(level=logging.DEBUG)

Next Steps

Once you understand this basic server, you can:

  1. Add Tools: Extend the server to expose callable functions
  2. Connect to Databases: Read data from real databases instead of static dictionaries
  3. Add Authentication: Secure your server with API keys or tokens
  4. Deploy: Run your server in production environments
  5. Integrate: Connect your server to Claude Desktop or other MCP clients

Resources

Happy MCP building! 🚀