Skip to content
DatabasesAuto-generatedScore: 46

AWS Database Migration Service MCP Server

AWS Database Migration Service (DMS), provided by Amazon Web Services, is a managed cloud service designed to facilitate seamless, secure, and highly available data migrations between a wide array of on-premises and cloud-based databases.

Quick Start Summary

The AWS Database Migration Service MCP server is a Model Context Protocol bridge that connects AI assistants — including Claude Desktop, Cursor, Windsurf, and VS Code Copilot — to the AWS Database Migration Service API through natural language. It exposes 10 API endpoints as callable tools, such as AddTagsToResource, ApplyPendingMaintenanceAction, BatchStartRecommendations, and more. No authentication is required — setup takes approximately 30 seconds. The server uses STDIO transport and can be installed by running npx -y @mcp/amazonaws-com-dms. This integration is sourced from the auto AWS Database Migration Service OpenAPI specification (v2016-01-01) and has a quality score of 46/99 (fair documentation coverage).

10Endpointstools mapped
NoneAuthopen access
46/99Qualityfair
~30 secSetupno auth

Server Details

Category
Databases
Authentication
None
Endpoints
10 operations
Transport
STDIO
Spec Version
v2016-01-01
Install Command
npx -y @mcp/amazonaws-com-dms

Environment Variables

AWS_DATABASE_MIGRATION_SERVICE_API_KEY

Example: your_aws_database_migration_service_api_key

Top Endpoints

POST
/#X-Amz-Target=AmazonDMSv20160101.AddTagsToResource

AddTagsToResource

POST
/#X-Amz-Target=AmazonDMSv20160101.ApplyPendingMaintenanceAction

ApplyPendingMaintenanceAction

POST
/#X-Amz-Target=AmazonDMSv20160101.BatchStartRecommendations

BatchStartRecommendations

POST
/#X-Amz-Target=AmazonDMSv20160101.CancelReplicationTaskAssessmentRun

CancelReplicationTaskAssessmentRun

POST
/#X-Amz-Target=AmazonDMSv20160101.CreateEndpoint

CreateEndpoint

Own this API?

Verify ownership of this listing to control the description, configuration details, and documentation links. Choose between free manual verification or instant premium placement.

Option 1: Free Verification

Slow manual review. Requires creating a GitHub issue with verified documentation or domain verification.

  • • Verified badge on page
  • • Standard search sorting
  • • 2-3 business days review
Start Free Claim →
Instant & Boosted

Option 2: Featured Upgrade($9/mo)

Instant verification plus premium styling, featured badges, and directory placement boost.

  • • ★ Featured star & amber highlight border
  • • Top of directory search placement
  • • Instant activation via claim token

📖 Detailed MCP Integration Guide

A technical breakdown of capabilities, agent workflows, and security/configuration best practices.

Capabilities & Use Cases
AWS Database Migration Service (DMS), provided by Amazon Web Services, is a managed cloud service designed to facilitate seamless, secure, and highly available data migrations between a wide array of on-premises and cloud-based databases. It supports heterogeneous migrations (e.g., from Oracle to PostgreSQL) and homogeneous migrations (e.g., from MySQL to Amazon Aurora MySQL) with minimal downtime for applications that depend on the source database. The service's core capabilities include continuous data replication for high availability and disaster recovery, schema conversion for logical database restructuring, and automated assessment of migration tasks. Typical enterprise use cases involve modernizing legacy database infrastructure by moving from on-premises systems to AWS cloud services like Amazon Aurora or Amazon Redshift, consolidating databases after mergers and acquisitions, and setting up hybrid architectures where data is replicated between on-premises data centers and the cloud for disaster recovery or low-latency access. For developers and data engineers, DMS provides a robust, scalable, and cost-effective solution to manage complex data migration projects that would otherwise require significant manual effort, custom scripting, and extended maintenance windows.
🤖AI Agent Value
When exposed as tools via the Model Context Protocol (MCP) to an AI coding assistant such as Claude Desktop, Cursor, or Cline, the AWS DMS API offers transformative value by abstracting the complexity of managing database migration infrastructure through natural language instructions. The AI agent can dynamically orchestrate the entire migration lifecycle by invoking specific endpoints, such as creating a replication instance with CreateReplicationInstance to provision the necessary compute resources, or defining source and target database connections using CreateEndpoint. This integration allows the AI to perform real-time monitoring and management tasks, such as querying the status of active replication tasks or cancelling long-running assessment runs with CancelReplicationTaskAssessmentRun if anomalies are detected. By surfacing DMS as a tool, developers can instruct the AI to automate repetitive operations—like applying pending maintenance actions via ApplyPendingMaintenanceAction to ensure databases remain compliant and up-to-date—or to batch-start recommendations with BatchStartRecommendations to optimize migration strategies. The AI can also manage organizational metadata by adding tags to resources with AddTagsToResource for cost allocation and governance, or by creating event subscriptions with CreateEventSubscription to set up proactive alerting for critical migration events.
💬Example Workflows
In a practical workflow, a developer might issue a command such as "Set up a migration from my on-premises PostgreSQL database to Amazon Aurora in the us-east-1 region, ensuring low downtime and continuous replication." The AI agent, leveraging the MCP server, would sequence the required API calls: first creating a replication subnet group with CreateReplicationSubnetGroup to define the network placement of the replication instance, then provisioning a ReplicationInstance, and finally creating source and target endpoints. Following this, the AI could initiate a migration task via CreateReplicationTask with settings configured for ongoing data replication. Another scenario could involve an instruction like "Generate a report of all pending maintenance actions across our DMS fleet and apply the high-priority ones." The AI would first query the current state, identify pending actions, and then invoke ApplyPendingMaintenanceAction selectively based on priority and impact. This dynamic, conversational interaction significantly accelerates development cycles, reduces the learning curve for new team members, and minimizes human error in managing critical data migration workflows.
🛡️Security & Auth
Crucially, while the API signature in the provided specification notes "None" for authentication, in practice all AWS API calls require proper authentication using AWS Signature Version 4, typically managed through AWS Identity and Access Management (IAM) credentials. Developers must create IAM roles and policies that adhere to the principle of least privilege, granting only the specific permissions necessary for the DMS tasks to be performed, such as dms:CreateReplicationInstance or dms:CreateEndpoint. It is a best practice to avoid using root account credentials and instead to use role-based access for programmatic access. Security configurations should also include enabling encryption for replication instances and endpoints, using SSL for data in transit, and storing sensitive database credentials in AWS Secrets Manager. When setting up the MCP server for integration with AI assistants, environment variables for AWS credentials should be securely managed and never committed to version control. Additionally, enabling CloudTrail logging for all DMS API activity ensures a comprehensive audit trail for compliance and security monitoring, providing visibility into all changes made to the migration environment.

Similar APIs

Other APIs in the Databases category.

PostgreSQL (MCP)

Query and manage PostgreSQL databases directly from your AI agent. Read schemas, run queries, and manage data.

Database Credentials

Notion API

The Notion API is a comprehensive RESTful interface provided by Notion, the popular all-in-one workspace platform, enabling programmatic interaction with its rich set of collaborative objects. It grants developers and automated systems the ability to read, create, update, and manage core Notion entities such as blocks (the fundamental building blocks of content like text, lists, and media), databases (structured tables with properties), pages (containers for content and databases), and comments. Typical use cases span enterprise and consumer scenarios, including automating team workflows, syncing data between Notion and other business systems (like CRM, project management, or analytics tools), building custom dashboards, generating dynamic reports, and enhancing content collaboration through programmatic updates. Organizations leverage this API to break down data silos, enforce process automation, and create tailored integrations that extend Notion's native capabilities for specific departmental or cross-functional needs.

Amazon CloudWatch Application Insights

Amazon CloudWatch Application Insights is a specialized observability service provided by Amazon Web Services (AWS) designed to simplify the monitoring and troubleshooting of applications, particularly those built on Microsoft IIS and .NET frameworks running on EC2 instances or within Elastic Beanstalk environments. Its core capability lies in automatically discovering application components, analyzing correlated metrics, logs, and traces to identify anomalies, and then surfacing actionable insights that pinpoint the root cause of common operational issues. By integrating seamlessly with other AWS services like CloudWatch, AWS X-Ray, and AWS Systems Manager, it provides a unified view of application health, reducing the mean time to resolution (MTTR) for performance degradations and errors. The typical use case spans enterprise environments managing distributed microservices or monolithic .NET applications, where teams need to proactively detect issues such as memory leaks, high CPU utilization, or specific application errors without manually configuring complex monitoring dashboards and alarms.

Application Auto Scaling

The Application Auto Scaling API, provided by Amazon Web Services (AWS), is a robust service designed to automate the scaling of computing resources for a wide array of AWS services, ensuring optimal performance, availability, and cost efficiency. Its core capability is to define policies that automatically adjust the provisioned capacity of supported resources in response to changing demand, as measured by CloudWatch metrics or predefined schedules. Beyond the initially listed resources, it supports scaling for Amazon DynamoDB tables and global secondary indexes, Amazon ECS services running on Fargate or EC2, Amazon ElastiCache replication groups, Amazon Neptune clusters, Amazon SageMaker endpoint variants, and custom resources via the AWS Lambda-backed scalable target. This makes it a central tool for architects and DevOps engineers in building resilient, self-optimizing cloud architectures. Typical enterprise use cases include dynamically adjusting the number of Aurora read replicas to handle database query load spikes, scaling ECS task counts during peak traffic for a microservices application, or optimizing costs by scaling down SageMaker inference endpoints during off-hours.

Related MCP Server Integrations

PostgreSQL (MCP) MCP Setup

Query and manage PostgreSQL databases directly from your AI agent. Read schemas, run queries, and manage data.

DatabasesConfigure →

Notion API MCP Setup

The Notion API is a comprehensive RESTful interface provided by Notion, the popular all-in-one workspace platform, enabling programmatic interaction with its rich set of collaborative objects. It grants developers and automated systems the ability to read, create, update, and manage core Notion entities such as blocks (the fundamental building blocks of content like text, lists, and media), databases (structured tables with properties), pages (containers for content and databases), and comments. Typical use cases span enterprise and consumer scenarios, including automating team workflows, syncing data between Notion and other business systems (like CRM, project management, or analytics tools), building custom dashboards, generating dynamic reports, and enhancing content collaboration through programmatic updates. Organizations leverage this API to break down data silos, enforce process automation, and create tailored integrations that extend Notion's native capabilities for specific departmental or cross-functional needs.

DatabasesConfigure →

Amazon CloudWatch Application Insights MCP Setup

Amazon CloudWatch Application Insights is a specialized observability service provided by Amazon Web Services (AWS) designed to simplify the monitoring and troubleshooting of applications, particularly those built on Microsoft IIS and .NET frameworks running on EC2 instances or within Elastic Beanstalk environments. Its core capability lies in automatically discovering application components, analyzing correlated metrics, logs, and traces to identify anomalies, and then surfacing actionable insights that pinpoint the root cause of common operational issues. By integrating seamlessly with other AWS services like CloudWatch, AWS X-Ray, and AWS Systems Manager, it provides a unified view of application health, reducing the mean time to resolution (MTTR) for performance degradations and errors. The typical use case spans enterprise environments managing distributed microservices or monolithic .NET applications, where teams need to proactively detect issues such as memory leaks, high CPU utilization, or specific application errors without manually configuring complex monitoring dashboards and alarms.

DatabasesConfigure →

Application Auto Scaling MCP Setup

The Application Auto Scaling API, provided by Amazon Web Services (AWS), is a robust service designed to automate the scaling of computing resources for a wide array of AWS services, ensuring optimal performance, availability, and cost efficiency. Its core capability is to define policies that automatically adjust the provisioned capacity of supported resources in response to changing demand, as measured by CloudWatch metrics or predefined schedules. Beyond the initially listed resources, it supports scaling for Amazon DynamoDB tables and global secondary indexes, Amazon ECS services running on Fargate or EC2, Amazon ElastiCache replication groups, Amazon Neptune clusters, Amazon SageMaker endpoint variants, and custom resources via the AWS Lambda-backed scalable target. This makes it a central tool for architects and DevOps engineers in building resilient, self-optimizing cloud architectures. Typical enterprise use cases include dynamically adjusting the number of Aurora read replicas to handle database query load spikes, scaling ECS task counts during peak traffic for a microservices application, or optimizing costs by scaling down SageMaker inference endpoints during off-hours.

DatabasesConfigure →

AWS Cost Explorer Service MCP Setup

The AWS Cost Explorer API, provided by Amazon Web Services, serves as the programmatic backbone for the Cost Explorer service, a powerful tool designed to help organizations visualize, understand, and manage their AWS cloud spending. At its core, this API enables developers and financial operations (FinOps) teams to move beyond the web console and directly query their cost and usage data, unlocking the ability to build custom dashboards, automated reports, and sophisticated cost management applications. Its capabilities range from retrieving high-level aggregated data, such as monthly service costs or daily usage totals, to drilling down into granular, resource-level details, including the specific write operations of a DynamoDB table or the data transfer metrics of an EC2 instance. This granular access is critical for enterprises implementing showback/chargeback models, identifying optimization opportunities, and enforcing budget guardrails across complex, multi-account AWS environments.

DatabasesConfigure →