"AWS cloud service monitoring" matching MCP servers:

This project builds a read-only MCP server. For full read, write, update, delete, and action capabilities and a simplified setup, check out our free CData MCP Server for Oracle Service Cloud (beta): https://www.cdata.com/download/download.aspx?sku=KOZK-V&type=beta

Enables visualization of Terraform plan changes as interactive cloud architecture diagrams with official AWS, Azure, and GCP icons, showing resource dependencies and changes.

Enables AI assistants to interact with AWS services and resources through AWS CLI commands, allowing management of AWS infrastructure with security controls.

Enables interaction with AWS services (EC2, S3, Lambda, DynamoDB, etc.) through the Model Context Protocol, allowing natural language management of cloud resources.

Enables users to generate professional AWS architecture diagrams, sequence diagrams, flow charts, and class diagrams using Python code through the diagrams package. Supports customizable styling and secure diagram generation for cloud infrastructure visualization.

Enables read-only querying of AWS accounts, regions, and resources through a small fixed set of MCP tools backed by a YAML catalog of views.

Enables AI clients to assess infrastructure-as-code deployment risk, generate incident response runbooks, review CI/CD delivery readiness, and calculate SLO error budgets through structured advisory tools. Runs locally over stdio without cloud credentials or external API calls, returning guidance for platform work, pull request review, and production readiness checks.

A small AWS MCP for AI assistants: one server, one config entry, SSO re-auth baked in, generic CRUD over hundreds of resource types, live docs lookup, server-side scripting for batched workflows.

Enables Claude Desktop and other MCP clients to list, read, export, and create Cloudcraft cloud-architecture blueprints, as well as snapshot AWS resources.

A simple MCP server that provides a basic greeting tool and serves as a starter template for AWS Lambda deployment. Demonstrates how to build and deploy MCP servers with both local development and cloud deployment capabilities.

MCP server for Azure Service Bus that enables sending messages, inspecting queues and subscriptions, and purging test data. Complements the built-in Azure MCP server by adding write operations.

Live operational status for 2,400+ major software services — AWS, GitHub, Stripe, OpenAI, Cloudflare, and more — pulled from each provider's official status page and returned as a normalised up / degraded / down result for any service you ask about.

A FastMCP server for Cursor platform APIs enabling spend guardrails, cloud agent monitoring, and inter-agent inbox messaging.

Lets AI agents draw professional cloud architecture diagrams with the official AWS, Azure and Google Cloud icons, from a plain description, a JSON graph or Terraform code.

A Model Context Protocol (MCP) server providing comprehensive cloud region data across all major providers. Query, filter, and compare cloud infrastructure locations worldwide.

MCP server exposing 3100+ cloud technology icons (AWS, Azure, GCP, Microsoft, CNCF, Devicon) with 3-tier search and multiple output formats for integration into presentations and architecture diagrams.

MCP server for deploying projects to multiple cloud platforms (Vercel, Railway, Neon, MongoDB Atlas, Docker) and running local dev servers, with orchestration for full-stack deployments.

A Model Context Protocol (MCP) server for LocalStack that enables management of local AWS development environments, including container lifecycle operations, infrastructure deployments, log analysis with IAM policy generation, chaos injection, and Cloud Pods state management.

Enables LLMs to search through AWS Lambda Powertools documentation across multiple runtimes (Python, TypeScript, Java, .NET) using a Model Context Protocol server.

Enables AI agents to manage Google Cloud Platform resources including projects, IAM, service accounts, and APIs directly through GCP REST APIs without requiring gcloud CLI or Terraform.