intric-mcp-template

inooLabs/intric-mcp-template

3.2

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The Intric MCP Template Server is designed to facilitate the creation of Model Context Protocol servers that integrate with Intric's MCP client, enhancing AI assistant capabilities.

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Resources
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Intric MCP Template Server

A template for building Model Context Protocol (MCP) servers that connect seamlessly with Intric's built-in MCP client. This template demonstrates how to create custom tools and resources that extend your AI assistant's capabilities.

Features

  • Tools: Functions the AI can call to perform actions
  • Resources: Static data the AI can access
  • Resource Templates: Dynamic resources based on parameters

Running the Server

Start the MCP server with HTTP transport:

python server.py

The server will start on http://localhost:8000 by default.

Connecting to Intric

Add your exposed server URL in Intric's MCP connections settings. Intric will automatically discover all available tools and resources.

Tip: You can use a service like ngrok to expose a https url binded to a local port and put that url (ending with /mcp) into Intric for testing.

Building Your Own MCP Server

Adding Tools

@mcp.tool
def your_function_name(param1: str, param2: int) -> str:
    """Description of what this tool does."""
    return f"Result: {param1} - {param2}"

Adding Resources

@mcp.resource("resource://your_resource_name")
def get_your_data() -> str:
    """Description of what data this resource provides"""
    return "Your data here"

Adding Resource Templates

@mcp.resource("data://{category}/{id}")
def get_dynamic_data(category: str, id: str) -> dict:
    """Provide data based on category and id."""
    return {"category": category, "id": id, "data": "..."}

Project Structure

intric-mcp-template/
├── server.py         # Main server file with examples
├── tools.py          # Example tool implementations
├── resources.py      # Example resource implementations
├── requirements.txt  # Python dependencies