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Welcome to AWS MCP Servers

Get started with AWS MCP Servers and learn core features.

The AWS MCP Servers are a suite of specialized MCP servers that help you get the most out of AWS, wherever you use MCP.

What is the Model Context Protocol (MCP) and how does it work with AWS MCP Servers?

The Model Context Protocol (MCP) is an open protocol that enables seamless integration between LLM applications and external data sources and tools. Whether you're building an AI-powered IDE, enhancing a chat interface, or creating custom AI workflows, MCP provides a standardized way to connect LLMs with the context they need.

Model Context Protocol README

An MCP Server is a lightweight program that exposes specific capabilities through the standardized Model Context Protocol. Host applications (such as chatbots, IDEs, and other AI tools) have MCP clients that maintain 1:1 connections with MCP servers. Common MCP clients include agentic AI coding assistants (like Q Developer, Cline, Cursor, Windsurf) as well as chatbot applications like Claude Desktop, with more clients coming soon. MCP servers can access local data sources and remote services to provide additional context that improves the generated outputs from the models.

AWS MCP Servers use this protocol to provide AI applications access to AWS documentation, contextual guidance, and best practices. Through the standardized MCP client-server architecture, AWS capabilities become an intelligent extension of your development environment or AI application.

AWS MCP servers enable enhanced cloud-native development, infrastructure management, and development workflows—making AI-assisted cloud computing more accessible and efficient.

The Model Context Protocol is an open source project run by Anthropic, PBC. and open to contributions from the entire community. For more information on MCP, you can find further documentation here

Why AWS MCP Servers?

MCP servers enhance the capabilities of foundation models (FMs) in several key ways:

  • Improved Output Quality: By providing relevant information directly in the model's context, MCP servers significantly improve model responses for specialized domains like AWS services. This approach reduces hallucinations, provides more accurate technical details, enables more precise code generation, and ensures recommendations align with current AWS best practices and service capabilities.

  • Access to Latest Documentation: FMs may not have knowledge of recent releases, APIs, or SDKs. MCP servers bridge this gap by pulling in up-to-date documentation, ensuring your AI assistant always works with the latest AWS capabilities.

  • Workflow Automation: MCP servers convert common workflows into tools that foundation models can use directly. Whether it's CDK, Terraform, or other AWS-specific workflows, these tools enable AI assistants to perform complex tasks with greater accuracy and efficiency.

  • Specialized Domain Knowledge: MCP servers provide deep, contextual knowledge about AWS services that might not be fully represented in foundation models' training data, enabling more accurate and helpful responses for cloud development tasks.

Getting Started Essentials

New from AWS New York Summit 2025!
Essential MCP servers for AWS resource management

Before diving into specific AWS services, set up these fundamental MCP servers for working with AWS resources:

Available AWS MCP Servers

The servers are organized into these main categories:

  • 📚 Documentation: Real-time access to official AWS documentation
  • 🏗️ Infrastructure & Deployment: Build, deploy, and manage cloud infrastructure
  • 🤖 AI & Machine Learning: Enhance AI applications with knowledge retrieval and ML capabilities
  • 📊 Data & Analytics: Work with databases, caching systems, and data processing
  • 🛠️ Developer Tools & Support: Accelerate development with code analysis and testing utilities
  • 📡 Integration & Messaging: Connect systems with messaging, workflows, and location services
  • 💰 Cost & Operations: Monitor, optimize, and manage your AWS infrastructure and costs
  • 🧬 Healthcare & Lifesciences: Interact with AWS HealthAI services.
Showing 52 of 52 servers
Documentation icon

AWS Documentation MCP Server

DocumentationVibe Coding & DevelopmentConversational Assistants

Get latest AWS docs and APIs

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AWS Knowledge MCP Server

DocumentationVibe Coding & DevelopmentConversational Assistants

Get latest AWS docs, code samples, and other official content

Core icon

AWS API MCP Server

CoreVibe Coding & Development

Interact with AWS services and resources through AWS CLI commands.

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AWS CDK MCP Server

Infrastructure & DeploymentVibe Coding & Development

AWS CDK development with security compliance

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AWS Terraform MCP Server

Infrastructure & DeploymentVibe Coding & Development

Terraform workflows with integrated security scanning

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AWS CloudFormation MCP Server

Infrastructure & DeploymentVibe Coding & Development

Direct CloudFormation resource management via Cloud Control API

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Amazon EKS MCP Server

Infrastructure & DeploymentVibe Coding & Development

Kubernetes cluster management and application deployment

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Amazon ECS MCP Server

Infrastructure & DeploymentVibe Coding & Development

Container orchestration and ECS application deployment

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Finch MCP Server

Infrastructure & DeploymentVibe Coding & Development

Local container building with ECR integration

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AWS Serverless MCP Server

Infrastructure & DeploymentVibe Coding & Development

Complete serverless application lifecycle with SAM CLI

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AWS Lambda Tool MCP Server

Infrastructure & DeploymentAutonomous Background Agents

Execute Lambda functions as AI tools for private resource access

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AWS Support MCP Server

Infrastructure & DeploymentConversational Assistants

Help users create and manage AWS Support cases

AI & Machine Learning icon

Amazon Bedrock Knowledge Bases Retrieval MCP Server

AI & Machine LearningConversational Assistants

Query enterprise knowledge bases with citation support

AI & Machine Learning icon

Amazon Kendra Index MCP Server

AI & Machine LearningConversational Assistants

Enterprise search and RAG enhancement

AI & Machine Learning icon

Amazon Q Business anonymous MCP Server

AI & Machine LearningConversational Assistants

AI assistant based on knowledgebase with anonymous access

AI & Machine Learning icon

Amazon Q index MCP Server

AI & Machine LearningConversational Assistants

Data accessors to search through enterprise's Q index

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Amazon Nova Canvas MCP Server

AI & Machine LearningConversational Assistants

AI image generation with text and color guidance

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Amazon Rekognition MCP Server

AI & Machine LearningConversational Assistants

Analyze images using computer vision capabilities

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Amazon Bedrock Data Automation MCP Server

AI & Machine LearningConversational Assistants

Analyze documents, images, videos, and audio files

Data & Analytics icon

Amazon DynamoDB MCP Server

Data & AnalyticsAutonomous Background Agents

Complete DynamoDB operations and table management

Data & Analytics icon

Amazon Aurora PostgreSQL MCP Server

Data & AnalyticsAutonomous Background Agents

PostgreSQL database operations via RDS Data API

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AWS S3 Tables MCP Server

Data & AnalyticsAutonomous Background Agents

Manage, query, and ingest S3-based tables with support for SQL, CSV-to-table conversion, and metadata discovery.

Data & Analytics icon

Amazon Aurora MySQL MCP Server

Data & AnalyticsAutonomous Background Agents

MySQL database operations via RDS Data API

Data & Analytics icon

Amazon Aurora DSQL MCP Server

Data & AnalyticsAutonomous Background Agents

Distributed SQL with PostgreSQL compatibility

Data & Analytics icon

Amazon DocumentDB MCP Server

Data & AnalyticsAutonomous Background Agents

MongoDB-compatible document database operations

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Amazon Neptune MCP Server

Data & AnalyticsAutonomous Background Agents

Graph database queries with openCypher and Gremlin

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Amazon Keyspaces MCP Server

Data & AnalyticsAutonomous Background Agents

Apache Cassandra-compatible operations

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Amazon Timestream for InfluxDB MCP Server

Data & AnalyticsAutonomous Background Agents

InfluxDB-compatible operations

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Amazon ElastiCache MCP Server

Data & AnalyticsAutonomous Background Agents

Complete ElastiCache operations

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Amazon ElastiCache / MemoryDB for Valkey MCP Server

Data & AnalyticsAutonomous Background Agents

Advanced data structures and caching with Valkey

Data & Analytics icon

Amazon ElastiCache for Memcached MCP Server

Data & AnalyticsAutonomous Background Agents

High-speed caching operations

Developer Tools & Support icon

Git Repo Research MCP Server

Developer Tools & SupportVibe Coding & Development

Semantic code search and repository analysis

Developer Tools & Support icon

Code Documentation Generation MCP Server

Developer Tools & SupportVibe Coding & Development

Automated documentation from code analysis

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AWS Diagram MCP Server

Developer Tools & SupportVibe Coding & Development

Generate architecture diagrams and technical illustrations

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Frontend MCP Server

Developer Tools & SupportVibe Coding & Development

React and modern web development guidance

Developer Tools & Support icon

Synthetic Data MCP Server

Developer Tools & SupportVibe Coding & Development

Generate realistic test data for development and ML

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OpenAPI MCP Server

Integration & MessagingVibe Coding & Development

Dynamic API integration through OpenAPI specifications

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Amazon SNS / SQS MCP Server

Integration & MessagingAutonomous Background Agents

Event-driven messaging and queue management

Integration & Messaging icon

Amazon MQ MCP Server

Integration & MessagingAutonomous Background Agents

Message broker management for RabbitMQ and ActiveMQ

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AWS Step Functions MCP Server

Integration & MessagingAutonomous Background Agents

Execute complex workflows and business processes

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Amazon Location Service MCP Server

Integration & MessagingConversational Assistants

Place search, geocoding, and route optimization

Cost & Operations icon

AWS Pricing MCP Server

Cost & OperationsConversational Assistants

Pre-deployment cost estimation and optimization

Cost & Operations icon

AWS Cost Explorer MCP Server

Cost & OperationsAutonomous Background AgentsConversational Assistants

Detailed cost analysis and reporting

Cost & Operations icon

AWS Managed Prometheus MCP Server

Cost & OperationsAutonomous Background Agents

Prometheus-compatible operations

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Core MCP Server

CoreVibe Coding & Development

Intelligent planning and AWS MCP server orchestration

Data & Analytics icon

Amazon Data Processing MCP Server

Data & AnalyticsAutonomous Background Agents

Comprehensive data processing tools and real-time pipeline visibility across AWS Glue and Amazon EMR-EC2

Healthcare & Lifesciences icon

AWS HealthOmics MCP Server

Healthcare & LifesciencesVibe Coding & Development

Generate, run, debug and optimize lifescience workflows on AWS HealthOmics

Cost & Operations icon

Amazon CloudWatch Application Signals MCP Server

Cost & OperationsAutonomous Background Agents

Application monitoring and performance insights

Cost & Operations icon

Amazon CloudWatch MCP Server

Cost & OperationsAutonomous Background Agents

Metrics, Alarms, and Logs analysis and operational troubleshooting

Developer Tools & Support icon

AWS IAM MCP Server

Developer Tools & SupportVibe Coding & Development

Comprehensive IAM user, role, group, and policy management with security best practices

Developer Tools & Support icon

AWS MSK MCP Server

Developer Tools & SupportAutonomous Background AgentsVibe Coding & Development

Manage, monitor, and optimize Amazon MSK clusters with best practices

Data & Analytics icon

Amazon Redshift MCP Server

Data & AnalyticsAutonomous Background Agents

Provides tools to discover, explore, and query Amazon Redshift clusters and serverless workgroups

When to use local vs remote MCP servers?

AWS MCP servers can be run either locally on your development machine or remotely on the cloud. Here's when to use each approach:

Local MCP Servers

  • Development & Testing: Perfect for local development, testing, and debugging
  • Offline Work: Continue working when internet connectivity is limited
  • Data Privacy: Keep sensitive data and credentials on your local machine
  • Low Latency: Minimal network overhead for faster response times
  • Resource Control: Direct control over server resources and configuration

Remote MCP Servers

  • Team Collaboration: Share consistent server configurations across your team
  • Resource Intensive Tasks: Offload heavy processing to dedicated cloud resources
  • Always Available: Access your MCP servers from anywhere, any device
  • Automatic Updates: Get the latest features and security patches automatically
  • Scalability: Easily handle varying workloads without local resource constraints

Note: Some MCP servers, like AWS Knowledge MCP, are provided as fully managed services by AWS. These AWS-managed remote servers require no setup or infrastructure management on your part - just connect and start using them.

Workflows

Each server is designed for specific use cases:

  • 👨‍💻 Vibe Coding & Development: AI coding assistants helping you build faster
  • 💬 Conversational Assistants: Customer-facing chatbots and interactive Q&A systems
  • 🤖 Autonomous Background Agents: Headless automation, ETL pipelines, and operational systems

Use Cases for the Servers

You can use the AWS Documentation MCP Server to help your AI assistant research and generate up-to-date code for any AWS service, like Amazon Bedrock Inline agents. Alternatively, you could use the CDK MCP Server or the Terraform MCP Server to have your AI assistant create infrastructure-as-code implementations that use the latest APIs and follow AWS best practices. With the Cost Analysis MCP Server, you could ask "What would be the estimated monthly cost for this CDK project before I deploy it?" or "Can you help me understand the potential AWS service expenses for this infrastructure design?" and receive detailed cost estimations and budget planning insights. The Valkey MCP Server enables natural language interaction with Valkey data stores, allowing AI assistants to efficiently manage data operations through a simple conversational interface.

Additional Resources