MCP Cloud Services Server
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Alternatives to MCP Cloud Services Server
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Related Servers
- AlicenseBqualityAmaintenanceEnables AI assistants to provision and manage cloud infrastructure and AI/ML workloads—such as GPUs, nodes, storage, networking, databases, Kubernetes, and training/inference resources—through natural language. It also provides a universal REST tool for authenticated access to the underlying cloud API.46Apache 2.0
- AlicenseNot gradedqualityCmaintenanceProvides AI agents with natural language control over AWS, Azure, GCP, and Alibaba Cloud infrastructure through dynamic API discovery and execution. Supports 51,900+ cloud operations and includes OpenTofu integration for complete infrastructure lifecycle management.3MIT

GreenNode MCP Serverofficial
AlicenseNot gradedqualityCmaintenanceEnables AI assistants to manage VNG Cloud infrastructure including compute, storage, networking, and Kubernetes resources through natural language commands.Apache 2.0- AlicenseNot gradedqualityDmaintenanceEnables AI assistants to perform DevOps tasks including Kubernetes management, cloud provider operations, CI/CD, security scanning, and infrastructure monitoring through natural language.MIT
- AlicenseNot gradedqualityDmaintenanceConnects AI assistants to AWS infrastructure through AWS IAM Identity Center for secure, natural language management of cloud resources across multiple accounts. It enables users to execute AWS CLI commands, monitor resources, and run remote shell commands on EC2 instances via Systems Manager.398 npm15ISC
- AlicenseNot gradedqualityCmaintenanceConnects AI assistants directly to Azure so users can manage infrastructure, resources, costs, security, and identities through plain-English conversation using their own Entra ID/RBAC permissions.MIT
TDQS
Scored across 26 tools
The tools have clear distinctions between cloud providers (AWS, Azure, GCP) and resource types, but there is significant overlap in functionality. For example, 'list_resources' appears to duplicate the purpose of provider-specific list tools like 'aws_list_ec2_instances' and 'azure_list_virtual_machines', which could confuse an agent about which tool to use for listing. Additionally, 'start_resource' and 'stop_resource' overlap with provider-specific start/stop tools like 'aws_start_ec2_instance', creating ambiguity in tool selection.
The naming conventions are inconsistent and mixed. Some tools use a 'provider_action_resource' pattern (e.g., 'aws_list_ec2_instances'), while others use a 'action_resource' pattern (e.g., 'list_resources', 'get_resource'). There is also variation in verb usage, such as 'analyze' vs. 'check' vs. 'scan', and some tools include provider prefixes while others do not. This lack of a predictable pattern makes the tool set harder to navigate and understand.
With 26 tools, the count is too high for the server's purpose of cloud services management. The duplication of functionality, such as having both generic and provider-specific list/start/stop tools, suggests bloat rather than necessity. A more streamlined set of 10-15 tools could cover the same domain effectively, making the current count feel heavy and potentially overwhelming for agents.
The tool set provides comprehensive coverage for cloud management, including listing, starting, stopping, analyzing costs, checking compliance, and scanning security issues across multiple providers. However, there are minor gaps, such as the absence of update or modify tools for resources (e.g., no 'update_resource' or 'modify_configuration'), which might require workarounds. Overall, the surface is largely complete for core operations.