MCI Python Adapter - Quickstart Guide

Welcome to the MCI Python Adapter! This guide will help you get started quickly with installing, configuring, and using the MCI (Model Context Interface) adapter to define and execute tools in your Python applications.

Installation

Prerequisites

Python 3.11 or higher
uv package manager (recommended) or pip

Option 1: Using uv (Recommended)

First, install uv if you haven’t already:

# macOS or Linux
curl -LsSf https://astral.sh/uv/install.sh | sh

# Or using Homebrew on macOS
brew install uv

Then install the MCI Python adapter:

# Install from PyPI
uv pip install mci-py

# Or install with uv add (if using uv project)
uv add mci-py

Option 2: Using pip

pip install mci-py

Verify Installation

import mcipy
print("MCI Python Adapter installed successfully!")

Quick Example

Here’s a complete example to get you started in under 5 minutes:

1. Create a Tool Schema File

Create a file named my-tools.mci.json:

{
  "schemaVersion": "1.0",
  "metadata": {
    "name": "My First Tools",
    "description": "A simple collection of tools"
  },
  "tools": [
    {
      "name": "greet_user",
      "description": "Generate a personalized greeting",
      "inputSchema": {
        "type": "object",
        "properties": {
          "username": {
            "type": "string",
            "description": "The user's name"
          }
        },
        "required": ["username"]
      },
      "execution": {
        "type": "text",
        "text": "Hello, {{props.username}}! Welcome to MCI."
      }
    },
    {
      "name": "get_weather",
      "description": "Fetch weather information",
      "inputSchema": {
        "type": "object",
        "properties": {
          "location": {
            "type": "string",
            "description": "City name"
          }
        },
        "required": ["location"]
      },
      "execution": {
        "type": "http",
        "method": "GET",
        "url": "https://api.example.com/weather",
        "params": {
          "location": "{{props.location}}"
        }
      }
    }
  ]
}

2. Write Python Code

Create a file named example.py:

from mcipy import MCIClient

# Initialize the client
client = MCIClient(
    schema_file_path="my-tools.mci.json",
    env_vars={
        "API_KEY": "your-secret-key"
    }
)

# List available tools
print("Available tools:")
for tool_name in client.list_tools():
    print(f"  - {tool_name}")

# Execute a tool
result = client.execute(
    tool_name="greet_user",
    properties={"username": "Alice"}
)

# Check the result
if result.result.isError:
    print(f"Error: {result.result.content[0].text}")
else:
    print(f"Success: {result.result.content[0].text}")

3. Run Your Code

python example.py

Output:

Available tools:
  - greet_user
  - get_weather
Success: Hello, Alice! Welcome to MCI.

What’s Next?

Now that you’ve seen the basics, explore these resources to learn more:

Basic Usage Guide - Detailed usage patterns and examples
Concepts - Understand MCI core concepts:
- Structure - Project structure and organization
- Tools - Different tool execution types
- Toolsets - Organizing and sharing tools
- MCP Servers - Integrating MCP servers
- Templates - Advanced templating features
Schema Reference - Complete schema documentation
API Reference - Detailed API documentation

Key Concepts at a Glance

Execution Types

MCI supports four execution types:

Text: Return templated text directly
File: Read file contents with template substitution
CLI: Execute command-line tools
HTTP: Make HTTP API requests

Template Placeholders

Use placeholders in your configurations:

{{props.fieldName}} - Access input properties
{{env.VARIABLE_NAME}} - Access environment variables

Tool Organization

Tools: Individual actions defined in your schema
Toolsets: Reusable collections of tools in separate files
MCP Servers: Integration with external MCP servers

Common Use Cases

API Integration: Use HTTP execution to integrate REST APIs
DevOps Automation: Use CLI execution for system tasks
Configuration Management: Use File execution for config templates
Reporting: Use Text execution for formatted reports
Data Processing: Combine multiple execution types

Getting Help

If you encounter issues or have questions:

Check the GitHub Issues
Review the PRD.md for design decisions
Examine the example.py for working code

Happy building with MCI! 🚀

Getting Started

Learn more

Python Quickstart Guide

MCI Python Adapter - Quickstart Guide

Installation

Prerequisites

Option 1: Using uv (Recommended)

Option 2: Using pip

Verify Installation

Quick Example

1. Create a Tool Schema File

2. Write Python Code

3. Run Your Code

What’s Next?

Key Concepts at a Glance

Execution Types

Template Placeholders

Tool Organization

Common Use Cases

Getting Help

​MCI Python Adapter - Quickstart Guide

​Installation

​Prerequisites

​Option 1: Using uv (Recommended)

​Option 2: Using pip

​Verify Installation

​Quick Example

​1. Create a Tool Schema File

​2. Write Python Code

​3. Run Your Code

​What’s Next?

​Key Concepts at a Glance

​Execution Types

​Template Placeholders

​Tool Organization

​Common Use Cases

​Getting Help

MCI Python Adapter - Quickstart Guide

Installation

Prerequisites

Option 1: Using uv (Recommended)

Option 2: Using pip

Verify Installation

Quick Example

1. Create a Tool Schema File

2. Write Python Code

3. Run Your Code

What’s Next?

Key Concepts at a Glance

Execution Types

Template Placeholders

Tool Organization

Common Use Cases

Getting Help