Building a Custom MCP Server

OmniMind’s strength lies in its flexibility to integrate custom MCP servers. This tutorial shows how to create a server that fetches data from an API.

Prerequisites

• OmniMind installed (Installation).

• Basic Python knowledge.

Step 1: Write the Server Script

Create api_server.py:

import requests
import sys

query = sys.argv[1] if len(sys.argv) > 1 else "default"
response = requests.get(f"https://api.example.com/data?q={query}")
print(response.json())

Step 2: Connect to OmniMind

Use OmniMind to run the server:

from omnimind import Agent

agent = Agent()
agent.add_server("api_server", command="python", args=["api_server.py"])
result = agent.run("search_term")
print(result)

This sends “search_term” to your server and prints the API response.

Step 3: Scale Up

Add multiple servers or integrate with Google Gemini. See Google Gemini Integration.

Share your server on GitHub!