Quickstart

Welcome to OmniMind! This Python library makes it easy and fun to work with MCP (Model Context Protocol) and AI. Whether you’re a beginner who’s never coded, a developer building projects, a solopreneur saving time, or a business owner adding smart tools, this guide gets you started in minutes. OmniMind connects you to MCP servers—helpers that fetch web info, manage files, or remember things—powered by Google Gemini for smart answers. Let’s dive in and make OmniMind shine on GitHub—maybe even as “repo of the day”!

Step 1: Install OmniMind

Before you begin, ensure you have OmniMind installed and a Google Gemini API key set up. See Installation for detailed instructions on installing OmniMind, setting the GOOGLE_API_KEY environment variable, and creating a config file (my_config.json) with default MCP servers (Fetch, Memory, Filesystem).

Step 2: Chat with OmniMind

Let’s start with the easiest way to use OmniMind—chatting with AI and MCP servers!

  1. Use Your Config File:

    Ensure you have a my_config.json file from Installation. It should look like this:

    {
    "mcpServers": {
        "fetch": {
            "command": "uvx",
            "args": ["mcp-server-fetch"]
        },
        "memory": {
            "command": "C:\\Program Files\\nodejs\\npx.cmd",
            "args": ["-y", "@modelcontextprotocol/server-memory"],
            "env": {
                "MEMORY_FILE_PATH": "C:\\Users\\YourName\\Desktop\\memory.json"
            }
        },
        "filesystem": {
            "command": "C:\\Program Files\\nodejs\\npx.cmd",
            "args": ["-y", "@modelcontextprotocol/server-filesystem", "C:\\Users\\YourName\\Desktop", "C:\\Users\\YourName\\Desktop\\workspace"]
        }
    }
}

    Replace YourName with your actual username (e.g., C:\\Users\\John\\Desktop). On Mac/Linux, use / (e.g., /home/john/Desktop).

    What’s Happening: This sets up Fetch (web info), Memory (saving data), and Filesystem (file tasks) servers.

  2. Create a Chat Script:

    Create a file named chat.py and add:

    from omnimind import OmniMind

agent = OmniMind(config_path="C:\\Users\\YourName\\Desktop\\my_config.json")
agent.run()

    Update the path to match where you saved my_config.json (e.g., /home/john/Desktop/my_config.json on Mac/Linux).

  3. Run and Chat:

    Open your terminal, navigate to the folder with chat.py (e.g., cd Desktop), and run:

    python chat.py

    You’ll see “Ready! Type ‘quit’ to exit.” Try typing: - “What’s on example.com?” (Fetch summarizes the webpage) - “Remember my favorite color is blue” (Memory saves it) - “List files in my directory” (Filesystem lists files)

    Type quit to stop.

Why It’s Great: You’re chatting with AI and MCP servers in minutes, it’s free, and it works for everyone—no coding experience needed!

Step 3: Do More with MCP Servers

Want to use OmniMind for bigger tasks? Try fetching web info, saving data, or managing files with the same config.

  1. Create a Multi-Task Script:

    Create a file named multi_task.py and add:

    from omnimind import OmniMind
import os

# Check API key
api_key = os.getenv("GOOGLE_API_KEY")
if not api_key:
    print("Please set the GOOGLE_API_KEY environment variable!")
    exit()

# Start OmniMind
agent = OmniMind(config_path="C:\\Users\\YourName\\Desktop\\my_config.json", api_key=api_key)
agent.run()

    Update the config path as before.

  2. Run and Try Tasks:

    Run with:

    python multi_task.py

    Type these prompts one by one: - “Summarize https://example.com” (Fetch gives a webpage summary) - “Remember my favorite color is blue” (Memory saves it) - “Create a file named example.txt” (Filesystem creates the file)

    Try more prompts like: - “Search for ‘function’ in all Python files” (Filesystem) - “Check Python version” (System command) - “What preferences did I set?” (Memory)

Why It’s Great: You can handle web, memory, and file tasks with one tool, it’s fast, and it’s all free and flexible.

Step 4: Explore More

Why It’s Great: OmniMind grows with you, it’s free to explore, and our community is here to help make it a top repo!