"AWS Organizations" matching MCP servers:

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

Enables AI assistants to execute SQL queries against AWS Athena databases, check query status, retrieve results, and manage saved queries with support for both local and remote deployment via Lambda.

MCP server for automated AWS security scanning — 19 modules, risk scoring, zero write operations.

Enables Claude to interact with core AWS services like S3, EC2, RDS, and CloudWatch, along with a generic SDK wrapper for any AWS operation. It also supports cost monitoring and optional vector store capabilities for document ingestion and search.

Enables interaction with multiple Azure DevOps organizations simultaneously, providing access to pipelines, builds, repositories, and pull requests across different organizations without switching contexts or restarting the server.

Enables evidence-first AWS architecture work through deterministic design calculations, live official AWS knowledge, integration catalog/configuration, and optional authenticated local read-only AWS tooling for requirements, comparisons, diagrams, ADRs, and operational planning.

Enables management and provisioning of AWS resources like EC2, S3, and RDS using natural language prompts through the Model Context Protocol. It allows users to automate complex infrastructure tasks, such as setting up VPCs and security groups, via a chat interface.

Provides a comprehensive suite of 76 tools for AWS cloud resource optimization, cost management, and infrastructure monitoring. It enables users to identify unused resources, analyze cost trends, right-size capacity, and maintain security compliance through natural language.

A Model Context Protocol server allowing Claude AI to interact with AWS resources through natural language, enabling users to query and manage AWS services without using the traditional AWS Console or CLI.

Enables analyzing AWS cloud spending and Bedrock usage through natural language queries using Claude.

A command-line interface and API that allows users to analyze and visualize AWS cloud spending data by enabling Claude to query AWS Cost Explorer through natural language conversations.

A unified MCP server for AWS that enables natural language infrastructure management, cross-service resource discovery, and dependency mapping. It features 30 intelligent tools for cost optimization, incident investigation, and multi-account operations protected by a robust safety system.

Enables read-only assessment of AWS environments by inventorying resources, running security and operational checks, and generating actionable reports with cost analysis. Designed for contractors with support for assume-role authentication using external IDs.

Automates the AWS Foundational Technical Review (FTR) partner self-assessment by evaluating SOC 2 and WAFR reports against defined controls, returning structured PASS/FAIL decisions with reasoning.

Enables Claude to create, list, inspect, and delete custom rowing workouts in the EXR indoor rowing app, converting intervals.icu workout documents (power, cadence, ramps, repeats) into EXR's simpler timed or distance-based blocks with dates in the titles. Runs as an AWS Lambda-hosted claude.ai custom connector with per-user OAuth sign-in, so several people can share one deployment while each only sees their own EXR workouts.

Enables Claude and other AI agents to read sleep and recovery data from a Fitbit or Pixel Watch through the Google Health API, including HRV, resting and sleeping heart rate, SpO2, breathing rate, skin temperature, and detailed sleep stages compared against a personal baseline. It runs as a shared AWS Lambda custom connector with per-user Google sign-in and read-only tools for recovery status, daily metrics, sleep sessions, and night-level detail.

A lightweight service that enables AI assistants to execute AWS CLI commands through the Model Context Protocol (MCP), allowing AI tools to retrieve AWS documentation and interact with AWS services.

A Model Context Protocol (MCP) server that enables AI assistants to perform comprehensive AWS security analysis through natural language queries, bridging AI with AWS security services.

Self-hosted memo knowledge base with MCP, REST, and read-only web interfaces; lets AI agents save and retrieve tagged, searchable study notes for AWS DevOps Pro exam prep.

Enables AI assistants to execute AWS CLI commands and retrieve service documentation through the Model Context Protocol. It supports Unix pipes for output filtering and provides pre-defined prompt templates for common cloud management tasks.

Enables users to analyze AWS costs, track spending trends, and detect anomalies directly within Claude Desktop using the AWS Cost Explorer API. It provides tools to identify major cost drivers and compare usage across different time periods through natural language queries.

Enables AI assistants to execute AWS CLI commands and access AWS documentation, resources, and prompt templates through the Model Context Protocol with support for Unix pipes and secure Docker-based deployment.

A framework to deploy MCP servers on AWS using serverless services like Lambda, API Gateway, and EventBridge, with dynamic tools, prompts, and resources managed via SSM parameters and Lambda functions.

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

Enables running a stateless Streamable HTTP MCP server on AWS Lambda behind API Gateway with JWT bearer authentication, per-scope tool allowlists, OAuth protected-resource metadata, and a CDK construct for deployment.

An MCP server that exposes AWS EC2 pricing data with an option to search by CPU, RAM, networking

Lets you inspect the health of your AWS Lambda functions and S3 buckets using plain English, with read-only access.

Enables natural-language analysis of AWS cloud spending and Amazon Bedrock model invocation usage, including breakdowns by service, region, day, user, model, and cross-account data.

Enables natural-language queries of AWS spending by service, region, day, and instance type, and of Amazon Bedrock usage from CloudWatch model-invocation logs, including optional cross-account cost analysis.

Enables natural-language querying and analysis of AWS spending and model-invocation usage, including detailed breakdowns by service, region, account, day, and instance type.

Enables users to query and analyze AWS cloud spending and Amazon Bedrock model usage through natural language, with breakdowns by day, region, service, instance type, user, and model, including cross-account cost visibility.

Enables natural-language queries of AWS spend and Bedrock usage data, providing detailed breakdowns by service, region, account, user, instance type, and model, including cross-account cost analysis.

Enables natural-language querying and visualization of cloud spending and Bedrock model invocation usage through MCP clients, with breakdowns by service, day, region, instance type, user, and model, including optional cross-account access.

A Model Context Protocol server that enables SQL queries and database exploration in AWS Athena through a standardized interface.

Enables natural-language analysis of AWS cloud spending by exposing Cost Explorer API functionality, including EC2, Bedrock, and per-service cost breakdowns by day, region, user, model, and instance type. It also retrieves Amazon Bedrock usage data from CloudWatch model invocation logs and can pull spend information from other accounts via assumed IAM roles.

Enables users to query and visualize AWS spend and Amazon Bedrock usage data through natural language, including EC2 and service cost breakdowns and Bedrock usage by region, user, and model.

Enables natural-language querying of AWS cloud spending and Amazon Bedrock usage logs, with detailed breakdowns by day, region, service, instance type, user, and model, including cross-account cost retrieval.

Enables natural-language analysis of AWS spend through Cost Explorer and Amazon Bedrock usage via CloudWatch model invocation logs, with breakdowns by service, region, model, user, day, and instance type. It also supports cross-account cost retrieval and local or remote MCP transports.

Enables users to query AWS spend data and Amazon Bedrock usage from CloudWatch model invocation logs through natural language. Supports detailed cost breakdowns by service, region, day, and instance type, including cross-account AWS spend retrieval.