MCP_ScopeGreen

The Model Context Protocol (MCP) server is designed to integrate the ScopeGreen API with various Language Learning Models (LLMs). This integration allows for the efficient exchange of data and commands between the API and LLMs, enabling advanced features such as real-time data processing, enhanced learning capabilities, and improved user interaction. The server acts as a bridge, ensuring that the LLMs can access and utilize the data provided by the ScopeGreen API effectively. By leveraging the MCP server, developers can create more robust and intelligent applications that benefit from the combined power of ScopeGreen's environmental data and the sophisticated processing abilities of LLMs.

Features

• Seamless Integration: Connects ScopeGreen API with LLMs for enhanced data processing.
• Real-time Data Processing: Enables LLMs to process and analyze data in real-time.
• Enhanced Learning Capabilities: Improves the learning and interaction capabilities of LLMs.
• User-friendly Interface: Provides an easy-to-use interface for developers to integrate and manage connections.
• Scalable Architecture: Supports scaling to accommodate growing data and user demands.

Usage with Different Platforms

python

python
import requests

url = 'https://scopegreen-main-1a948ab.d2.zuplo.dev/api/integrate'
headers = {'Authorization': 'Bearer YOUR_API_KEY'}

response = requests.get(url, headers=headers)

if response.status_code == 200:
    data = response.json()
    print('Integration successful:', data)
else:
    print('Failed to integrate:', response.status_code)

nodejs

javascript
const axios = require('axios');

const url = 'https://scopegreen-main-1a948ab.d2.zuplo.dev/api/integrate';
const headers = { 'Authorization': 'Bearer YOUR_API_KEY' };

axios.get(url, { headers })
  .then(response => {
    console.log('Integration successful:', response.data);
  })
  .catch(error => {
    console.error('Failed to integrate:', error.response.status);
  });