Can one agent manage both clouds at once?

Yes — register both servers and the agent can call Azure's service tools and the AWS CLI tool in the same session. Each uses its own cloud credentials, so you scope permissions independently per cloud.

Why does AWS use one tool while Azure uses many?

AWS Labs leans on the maturity and completeness of the AWS CLI, exposing it through a single validated tool, whereas Microsoft generates a distinct tool per Azure service so the model can target each surface directly. Both reach broad functionality by different routes.

Azure vs AWS (AWS Labs)

Both of these are official, first-party MCP servers from the two largest public clouds, and both let an AI agent operate your cloud account conversationally using your own credentials and IAM/RBAC for authorization. Microsoft's Azure MCP Server takes a breadth-first approach: it ships a single package that exposes more than forty distinct Azure services as named tools — storage, Key Vault, Cosmos DB, SQL, Monitor, AKS, App Service, and many more — so the agent reaches each service through a purpose-built surface. The AWS Labs server takes the opposite approach for the same goal: rather than one tool per service, the general-purpose AWS API MCP server gives the agent a single typed surface over the entire AWS CLI, validating and executing any aws command and even suggesting the right command from a natural-language description. If you live in one cloud, the choice is made for you; if you straddle both, the interesting difference is breadth-of-services-as-tools versus depth-of-one-CLI-as-tool. Here is how the two compare when you wire an agent into your cloud.

How they compare

Dimension	Azure	AWS (AWS Labs)
Tool model	One named tool per Azure service — storage, keyvault, cosmos, sql, monitor, aks, appservice, and ~40 more — so the agent picks the right service surface explicitly.	A single call_aws tool that validates and runs any AWS CLI command, plus suggest_aws_commands to translate intent into the correct command and get_execution_plan for multi-step plans.
Service coverage	Forty-plus Azure services in one package: Cosmos DB, Key Vault, AKS, App Service, Functions, Service Bus, Event Hubs, Kusto, Monitor/Log Analytics, plus deploy and Bicep/Terraform helpers.	Effectively the entire AWS API, because anything the AWS CLI can do, the agent can do — the catch is the model must know the right command, which the suggest tool helps with.
Distribution	Microsoft's official @azure/mcp npm package (also a Docker image), launched with npx -y @azure/mcp@latest server start over stdio.	AWS Labs' open-source suite — sixty-plus specialized servers exist, but this general-purpose API server is the broadest entry point and the recommended starting place.
Auth and safety	Uses your Azure credentials and Azure RBAC, so the agent inherits exactly the permissions of the identity you authenticate with.	Uses your AWS credentials and IAM; ships command validation and a read-only mode so you can prevent the agent from executing mutating commands.
Best-fit task	Teams already on Azure who want discoverable, service-named tools the model can reason about without knowing CLI syntax.	Teams already on AWS who are comfortable with the AWS CLI mental model and want one tool that reaches every service, with command suggestions filling the knowledge gap.

Verdict

Pick by which cloud your infrastructure already lives in — neither server is a reason to migrate. Both are official, both authenticate with your own credentials, and both respect the cloud's native authorization model. The real design difference is shape: Azure exposes forty-plus services as discrete, named tools, which is easier for a model to reason about service-by-service, while the AWS API server collapses everything into one CLI-executing tool plus a command-suggester, which is maximally broad but leans on the model knowing (or being told) the right aws invocation. Choose Azure's server on Azure; choose the AWS API server on AWS, and enable its read-only mode when you want the agent to investigate without changing anything.

FAQ

Can one agent manage both clouds at once?: Yes — register both servers and the agent can call Azure's service tools and the AWS CLI tool in the same session. Each uses its own cloud credentials, so you scope permissions independently per cloud.
Why does AWS use one tool while Azure uses many?: AWS Labs leans on the maturity and completeness of the AWS CLI, exposing it through a single validated tool, whereas Microsoft generates a distinct tool per Azure service so the model can target each surface directly. Both reach broad functionality by different routes.