data-ai MCP Server
๐ Manage multi-cloud resources seamlessly with poly-cloud-mcp, leveraging Model Context Protocol tools for AWS, Google Cloud, Azure, and DigitalOcean.
Discovered via github-topic:model-context-protocol and last synced 3mo ago.
1. Install the package
npm install poly-cloud-mcp
Detecting exposed AWS credentials in source code repositories, CI/CD pipelines, and configuration files using TruffleHog, git-secrets, and AWS-native detection mechanisms to prevent credential theft and unauthorized account access.
Auditing Microsoft Entra ID (Azure Active Directory) configuration to identify risky authentication policies, overly permissive role assignments, stale accounts, conditional access gaps, and guest user risks using AzureAD PowerShell, Microsoft Graph API, and ScoutSuite.
Detecting data exfiltration attempts from AWS S3 buckets by analyzing CloudTrail S3 data events, VPC Flow Logs, GuardDuty findings, Amazon Macie alerts, and S3 access patterns to identify unauthorized bulk downloads and cross-account data transfers.
Implementing AWS Security Hub to aggregate security findings across AWS accounts, enable compliance standards like CIS AWS Foundations and PCI DSS, configure automated remediation with EventBridge and Lambda, and create custom security insights for organizational risk management.
Sample code and notebooks for Generative AI on Google Cloud, with Gemini Enterprise Agent Platform
Flexible and powerful framework for managing multiple AI agents and handling complex conversations
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Labs to explore AI Models, MCP servers, and Agents with the AI Gateway powered by Azure API Management and Microsoft Foundry ๐
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