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Cloud-provider MCP servers that let Claude manage cloud resources, compared on trust, platforms, and setup.

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FieldAWS Services MCP Server - MCP Servers

Comprehensive AWS cloud services integration for infrastructure management, deployment, and monitoring

Open dossier 		Azure MCP Server for Claude

Official Microsoft Azure MCP server that connects Claude and other MCP clients to Azure subscriptions, resource groups, storage, databases, Key Vault, Monitor, App Service, AKS, AI Search, Cosmos DB, RBAC, pricing, and other Azure services through local stdio or self-hosted HTTP transports.

Open dossier 		gcloud MCP Server

Google Cloud gcloud MCP server from googleapis that lets Claude run approved gcloud CLI commands with allowlist and denylist controls for cloud resource inspection, automation, and operations.

Open dossier
Trust
Install riskLow riskReview firstReview first
Notes Safety ✓ Privacy ✓ Safety ✓ Privacy ✓ Safety ✓ Privacy ✓
Categorymcpmcpmcp
Sourcefirst-partysource-backedsource-backed
AuthorAWS LabsMicrosoftGoogle APIs
Added2025-09-162026-06-042026-06-06
Platforms
Claude CodeClaude Desktop
Claude CodeClaude Desktop
Claude CodeClaude Desktop
Source repo———
Safety notes✓Scope AWS credentials to the intended accounts, regions, and services because infrastructure actions can affect production resources.✓Start in read-only mode and narrow the exposed namespaces or individual tools before enabling broader Azure access. Microsoft documents read-only mode, namespace filters, single-tool mode, and learn mode as controls for reducing the active MCP surface. Azure MCP tools can inspect and manage real cloud resources. Depending on the tool and RBAC role, actions can create, update, delete, deploy, restart, query, or reconfigure resources and can incur cloud spend. Keep human approval on destructive, cost-bearing, deployment, RBAC, Key Vault, database, storage, messaging, and production-environment actions. Do not disable user confirmation for high-risk or sensitive-data commands unless the automation environment is tightly controlled. The server authenticates with Azure credentials available to the local machine or hosted environment. Limit the credential chain with `AZURE_TOKEN_CREDENTIALS`, managed identities, service principals, and least-privilege Azure RBAC where practical. For self-hosted HTTP deployments, configure Entra ID inbound authentication, outbound authentication strategy, network exposure, logging, and per-user versus server-identity audit requirements before sharing the endpoint. Docker setup uses Azure credential environment variables such as `AZURE_TENANT_ID`, `AZURE_CLIENT_ID`, and `AZURE_CLIENT_SECRET`; protect those values and never commit the env file. Microsoft documents telemetry environment variables for the server. Review `AZURE_MCP_COLLECT_TELEMETRY` and `AZURE_MCP_COLLECT_TELEMETRY_MICROSOFT` before using the server in sensitive environments. This is the Azure services MCP server. It is distinct from the Azure DevOps MCP server, which focuses on work items, repositories, pull requests, pipelines, wikis, and test plans.✓gcloud MCP Server executes gcloud CLI commands with the permissions of the active gcloud account. Allowed commands can create, update, delete, deploy, scale, list, export, or configure Google Cloud resources depending on IAM permissions and selected services. The server blocks command substitution, pipes, redirection, SSH-style commands, interactive commands, and a default set of sensitive command prefixes, but allowed gcloud commands can still have real infrastructure, billing, IAM, and data impact. Use allowlists for narrow workflows and service account impersonation with limited roles when possible. Require human approval for IAM, billing, networking, firewall, storage, database, secret, deployment, delete, and production-impacting commands.
Privacy notes✓AWS resource names, configuration, metrics, logs, ARNs, and account metadata may be exposed through tool calls and responses.✓Tool results can expose tenant IDs, subscription IDs, resource groups, resource names, tags, deployment outputs, Azure Monitor logs, metrics, pricing data, quotas, RBAC assignments, policy data, app settings, database metadata, storage account and blob metadata, and service-specific configuration. Key Vault, App Configuration, Storage, database, Service Bus, Event Hubs, Communication Services, and deployment tools may expose secrets, connection strings, keys, certificates, message contents, sample records, or customer data when the authenticated identity has permission. Microsoft documents user confirmation for tools that handle sensitive data, including Key Vault secrets, connection strings, passwords, certificate private keys, and other confidential values. Treat those prompts as a required guardrail rather than friction. MCP client logs, AI transcripts, local terminal history, hosted server logs, prompt traces, generated runbooks, and downstream tickets can retain Azure resource inventory and returned data outside Azure's original access and retention boundaries. Remote HTTP deployments require Entra ID bearer tokens on inbound requests and a configured outbound Azure authentication strategy. Choose On-Behalf-Of when per-user RBAC and audit trails matter, and managed identity only when the shared-server identity model is acceptable. Read-only mode reduces mutation risk, but it does not make returned Azure metadata or data safe to share with untrusted models, logs, chats, or third-party tools.✓gcloud output can reveal project IDs, resource names, regions, IAM bindings, service accounts, logs, errors, labels, metadata, URLs, secrets references, billing context, and infrastructure topology. Authentication state, ADC files, service account impersonation details, access tokens, project IDs, and local gcloud configuration should stay out of prompts and repository files. Command output may be retained by the MCP client, model provider, terminal logs, shell history, and chat transcripts. Avoid broad listing or export commands against production projects unless data handling and retention have been reviewed.
Prerequisites
  • Python 3.8+ installed for running uvx commands
  • uv package manager installed (provides uvx command for running Python packages)
  • AWS account with active credentials and appropriate IAM permissions
  • AWS credentials configured via one of: IAM access keys (AWS_ACCESS_KEY_ID, AWS_SECRET_ACCESS_KEY), AWS profile (~/.aws/credentials), or IAM role (for EC2/ECS)
  • Azure subscription, tenant, and RBAC permissions for the resources Claude should inspect or manage.
  • MCP-capable client that can run local stdio servers or connect to a self-hosted HTTP MCP endpoint.
  • Azure authentication through Azure CLI, Azure PowerShell, Visual Studio, Visual Studio Code, Azure Developer CLI, browser login, service principal environment variables, workload identity, or managed identity.
  • Node.js 20 LTS or later and `npx` for the `@azure/mcp` package, or `uvx` for `msmcp-azure`, or .NET 10 Preview 6 or later for `Azure.Mcp`.
  • Node.js 20 or newer with npm or another compatible package runner.
  • Google Cloud CLI installed and authenticated.
  • Active gcloud account, project, and configuration scoped to the intended environment.
  • Least-privilege user or service account impersonation for the allowed cloud actions.
Install
uvx awslabs.core-mcp-server@latest && claude mcp list
npx -y @azure/mcp@latest server start
npx -y @google-cloud/gcloud-mcp
Config
{
  "mcpServers": {
    "aws": {
      "env": {
        "AWS_REGION": "${AWS_REGION:-us-east-1}",
        "AWS_PROFILE": "${AWS_PROFILE}",
        "FASTMCP_LOG_LEVEL": "${FASTMCP_LOG_LEVEL:-ERROR}"
      },
      "args": [
        "awslabs.core-mcp-server@latest"
      ],
      "command": "uvx",
      "type": "stdio"
    }
  }
}
{
  "mcpServers": {
    "Azure MCP Server": {
      "command": "uvx",
      "args": [
        "--from",
        "msmcp-azure",
        "azmcp",
        "server",
        "start"
      ]
    }
  }
}
{
  "mcpServers": {
    "gcloud": {
      "command": "npx",
      "args": [
        "-y",
        "@google-cloud/gcloud-mcp"
      ],
      "type": "stdio"
    }
  }
}
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