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Manage multi-cloud resources through one interface across major cloud platforms.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "poly-cloud-mcp" yet — see the docs or source repo.
Using poly-cloud-mcp, list the currently running compute instances in AWS, Google Cloud, Azure, and DigitalOcean. Group them by provider and include instance name, region, and status.
A provider-grouped list of running instances with names, regions, and statuses.
Use poly-cloud-mcp to inspect buckets across AWS S3, Google Cloud Storage, Azure Blob Storage, and DigitalOcean Spaces, and identify publicly accessible resources or ones missing basic tags.
A multi-cloud storage audit report listing buckets and potential configuration issues.
Through poly-cloud-mcp, count key resources across AWS, GCP, Azure, and DigitalOcean, including virtual machines, object storage, and Kubernetes clusters, then output a concise summary table.
A concise multi-cloud summary table showing resource distribution across providers.
Connect AI assistants to AWS resources and workflows through open-source MCP servers.
Parse multi-cloud IaC and generate real-time cost estimates and comparisons.
Create and manage AWS infrastructure resources through an MCP server.
Query core Azure services through one interface for development and operations.
Manage Azure infrastructure and cloud resources using natural language commands.
Route multi-cloud MCP requests and surface only the most relevant tools.