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Cloud InfrastructureAuto-generatedScore: 46

AWS Secrets Manager MCP Server

Amazon Web Services Secrets Manager is a fully managed service designed to centralize the secure lifecycle management of sensitive information such as database credentials, API keys, OAuth tokens, and other confidential configuration data.

Quick Start Summary

The AWS Secrets Manager MCP server is a Model Context Protocol bridge that connects AI assistants — including Claude Desktop, Cursor, Windsurf, and VS Code Copilot — to the AWS Secrets Manager API through natural language. It exposes 10 API endpoints as callable tools, such as CancelRotateSecret, CreateSecret, DeleteResourcePolicy, 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-secretsmanager. This integration is sourced from the auto AWS Secrets Manager OpenAPI specification (v2017-10-17) and has a quality score of 46/99 (fair documentation coverage).

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

Server Details

Category
Cloud Infrastructure
Authentication
None
Endpoints
10 operations
Transport
STDIO
Spec Version
v2017-10-17
Install Command
npx -y @mcp/amazonaws-com-secretsmanager

Environment Variables

AWS_SECRETS_MANAGER_API_KEY

Example: your_aws_secrets_manager_api_key

Top Endpoints

POST
/#X-Amz-Target=secretsmanager.CancelRotateSecret

CancelRotateSecret

POST
/#X-Amz-Target=secretsmanager.CreateSecret

CreateSecret

POST
/#X-Amz-Target=secretsmanager.DeleteResourcePolicy

DeleteResourcePolicy

POST
/#X-Amz-Target=secretsmanager.DeleteSecret

DeleteSecret

POST
/#X-Amz-Target=secretsmanager.DescribeSecret

DescribeSecret

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📖 Detailed MCP Integration Guide

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

Capabilities & Use Cases
Amazon Web Services Secrets Manager is a fully managed service designed to centralize the secure lifecycle management of sensitive information such as database credentials, API keys, OAuth tokens, and other confidential configuration data. It eliminates the need for developers to hardcode secrets directly into application code or configuration files, thereby significantly reducing the risk of accidental exposure. The service provides robust capabilities for storing, retrieving, rotating, and revoking secrets on demand. Enterprises rely on this service to enforce consistent security policies, simplify credential management across distributed applications, and maintain detailed audit trails of secret access and changes through integration with AWS CloudTrail. It is a foundational component for building secure, scalable applications on AWS and is frequently used by development, security, and DevOps teams to manage secrets for microservices, databases, and third-party service integrations.
🤖AI Agent Value
When exposed as tools to an AI coding assistant via the Model Context Protocol, the AWS Secrets Manager API becomes exceptionally powerful for automating security and configuration tasks. An AI agent can act as a knowledgeable security operator, directly interacting with the secret store to enhance developer productivity and enforce best practices. For instance, the AI could dynamically fetch a database connection string needed to execute a query or run a migration script, completely abstracting the secret handling from the developer's workflow. It could also audit the secret inventory, checking for secrets that are misconfigured, lack rotation policies, or have not been accessed within a defined period. By having programmatic, contextual access to the secret store, the AI assistant transitions from a passive code generator to an active participant in maintaining the security posture and operational resilience of the application.
💬Example Workflows
Practical workflows enabled by this integration are numerous. A developer could instruct the AI to "retrieve the API key for the payment gateway and use it to test the new checkout endpoint," allowing the AI to securely fetch the secret and incorporate it into a test script without manual intervention. For automation, one could command, "Check the last rotated date for all database secrets in production and generate a rotation schedule for any that are older than 90 days," turning the AI into a proactive compliance agent. During development, a task like "Create a new secret named 'dev/staging-cache-credentials' with the value I provide and attach the policy allowing read access to the 'developer' role" can be executed conversationally. Furthermore, the AI could be instructed to "list all secrets tagged with 'application:web-api' and summarize their rotation settings and last access timestamps," providing an instant security overview.
🛡️Security & Auth
Critical security best practices must be followed when configuring this MCP server. The authentication method for the underlying API relies on AWS IAM policies; therefore, the credentials used by the AI agent must be governed by the principle of least privilege. The IAM user or role should only have permissions for the specific secret operations required, such as secretsmanager:GetSecretValue for only certain secret ARNs, rather than broad administrative access. Developers should employ IAM conditions to restrict access to specific IP ranges or VPC endpoints. It is strongly recommended to use resource-based policies on individual secrets for fine-grained control. All actions should be logged via CloudTrail for auditing. Secret values should never be embedded in logs or output; the AI tool must be configured to handle secrets in memory only. Regular rotation of secrets using the built-in Lambda rotation feature is essential, and the AI should be aware of rotation schedules to avoid fetching stale credentials.

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