data-ai MCP Server
Manage AWS, Hetzner, OVH, and custom servers from one TUI — with a built-in AI assistant and MCP server
Discovered via github-topic:mcp and last synced 3mo ago.
Install instructions not detected yet
Check the source repository for the latest setup steps.
Update Servonaut (when update available)
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Tools
pin
Browse remote files
Find/search in output
Purpose
Key
SCP transfer
Behavior
`Ctrl+C`
`ovh_monitoring`, `ovh_list_ips`, `ovh_firewall_rules`, `ovh_ssh_keys`, `ovh_snapshots`, `ovh_dns_records`, `ovh_billing`, `ovh_invoices`, `ovh_create_instance`, `ovh_delete_instance`, `ovh_start_instance`, `ovh_stop_instance`, `ovh_reboot_instance`
show
Required Permissions
`F2`
Force-refresh from AWS
SSH to selected instance
Clear output
Pause/resume streaming
Switch log file
`relay_status`, `relay_reconnect`, `mcp_tool_call`
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.
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.
Implement Amazon Macie to automatically discover, classify, and protect sensitive data in S3 buckets using machine learning and pattern matching for PII, financial data, and credentials detection.
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.
Flexible and powerful framework for managing multiple AI agents and handling complex conversations
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