Google Drive Storage for MCP Servers

Learn how to implement Google Drive storage integration for Model Context Protocol servers

Google Drive Storage Integration for MCP

Overview

Google Drive storage provides a reliable cloud-based solution for storing and managing model context data in MCP servers. This guide explains how to integrate Google Drive API with your MCP server implementation.

Prerequisites

Google Cloud Platform account
Google Drive API enabled
Service account with appropriate permissions
Node.js 18 or higher
MCP server base implementation

Setting Up Google Drive API

Create a new project in Google Cloud Console
Enable the Google Drive API
Create service account credentials
Download the credentials JSON file

Installation

npm install @google-cloud/storage googleapis

Implementation

import { google } from 'googleapis';
import { JWT } from 'google-auth-library';

class GoogleDriveStorage implements MCPStorageProvider {
  private drive: any;
  private folderId: string;

  constructor(credentials: any, folderId: string) {
    const auth = new JWT({
      email: credentials.client_email,
      key: credentials.private_key,
      scopes: ['https://www.googleapis.com/auth/drive']
    });

    this.drive = google.drive({ version: 'v3', auth });
    this.folderId = folderId;
  }

  async storeContext(contextId: string, data: Buffer): Promise<void> {
    await this.drive.files.create({
      requestBody: {
        name: `${contextId}.ctx`,
        parents: [this.folderId],
        mimeType: 'application/octet-stream'
      },
      media: {
        mimeType: 'application/octet-stream',
        body: data
      }
    });
  }

  async retrieveContext(contextId: string): Promise<Buffer> {
    const files = await this.drive.files.list({
      q: `name='${contextId}.ctx' and '${this.folderId}' in parents`,
      fields: 'files(id)'
    });

    if (!files.data.files.length) {
      throw new Error('Context not found');
    }

    const response = await this.drive.files.get({
      fileId: files.data.files[0].id,
      alt: 'media'
    }, { responseType: 'arraybuffer' });

    return Buffer.from(response.data);
  }
}

Configuration

const storage = new GoogleDriveStorage({
  client_email: process.env.GOOGLE_CLIENT_EMAIL,
  private_key: process.env.GOOGLE_PRIVATE_KEY
}, process.env.GOOGLE_DRIVE_FOLDER_ID);

const mcpServer = new MCPServer({
  storage
});

Error Handling

try {
  await storage.storeContext('model-123', contextBuffer);
} catch (error) {
  if (error.code === 404) {
    console.error('Folder not found');
  } else if (error.code === 403) {
    console.error('Permission denied');
  } else {
    console.error('Storage error:', error);
  }
}

Best Practices

Folder Structure: Organize contexts in separate folders based on model types or versions
Backup Strategy: Implement regular backups of critical context data
Rate Limiting: Handle Google Drive API quotas and implement rate limiting
Caching: Consider implementing a local cache for frequently accessed contexts

Security Considerations

Use service accounts with minimal required permissions
Store credentials securely using environment variables
Implement encryption for sensitive context data
Regular audit of stored contexts and access patterns

Performance Optimization

Implement batch operations for multiple contexts
Use compression for large context files
Monitor API usage and implement retries with exponential backoff

Monitoring

class MonitoredGoogleDriveStorage extends GoogleDriveStorage {
  async storeContext(contextId: string, data: Buffer): Promise<void> {
    const startTime = Date.now();
    try {
      await super.storeContext(contextId, data);
      metrics.recordStorageOperation('store', Date.now() - startTime);
    } catch (error) {
      metrics.recordStorageError('store');
      throw error;
    }
  }
}

Testing

describe('GoogleDriveStorage', () => {
  it('should store and retrieve context', async () => {
    const storage = new GoogleDriveStorage(credentials, folderId);
    const contextId = 'test-123';
    const testData = Buffer.from('test data');
    
    await storage.storeContext(contextId, testData);
    const retrieved = await storage.retrieveContext(contextId);
    
    expect(retrieved.toString()).toBe(testData.toString());
  });
});

Resources

Brave Search Kagi MCP Server

VSCode Extension Development MCP Servers

Cloud Foundry and MCP Integration

Cloud Foundry integration with Model Context Protocol (MCP) enables advanced PaaS capabilities, automated deployments, and streamlined service management. This implementation provides robust application lifecycle management, service integration, and monitoring features for modern cloud-native applications.