The AWS MCP Server is now generally available | Amazon Web Services
The AWS MCP Server is now generally available as a managed way for AI agents to access AWS securely through IAM-authenticated tools. It combines live AWS documentation, access to more than 15,000 API operations, and sandboxed scripting so agents can produce more current, efficient, and production-ready results. The post concludes that this solves major limitations of model-only AWS assistance without granting agents unrestricted credentials. ## Why AI Agents Struggle with AWS - Models may lack knowledge of recently launched services such as Amazon S3 Vectors, Aurora DSQL, and Bedrock AgentCore. - Agents often default to the AWS CLI instead of AWS CDK or CloudFormation. - Generated IAM policies are frequently broader than necessary. - The resulting infrastructure may work in demos but fail production standards. ## Core AWS MCP Server Tools - `call_aws` can execute more than 15,000 AWS API operations using the user’s existing IAM credentials. - `search_documentation` and `read_documentation` retrieve current AWS documentation and best practices at query time. - The compact tool set reduces model context usage and is intended to support newly launched APIs within days. ## General Availability Improvements - IAM context keys allow fine-grained access control through standard IAM policies without requiring a separate server permission. - Documentation retrieval no longer requires authentication. - Reduced token consumption improves complex, multi-step workflows. - The `run_script` tool executes short Python scripts in a server-side sandbox. - The sandbox inherits IAM permissions. - It has no network access or access to the user’s local filesystem and shell. - It can combine multiple API calls, filter results, and calculate outputs in one round trip. ## Skills and AWS Best Practices - Skills replace Agent SOPs with curated guidance for common AWS tasks. - AWS service teams contribute and maintain the Skills. - They help agents avoid mistakes, use validated patterns, reduce hallucinations, and consume fewer tokens. - Keeping the tool list small makes agent behavior more predictable. ## Enterprise Security and Observability - IAM policies and Service Control Policies can separate human permissions from agent permissions. - For example, a user may perform write operations while the MCP server is restricted to read-only access. - CloudWatch metrics under the `AWS-MCP` namespace distinguish agent activity from direct human calls. - AWS CloudTrail records all API calls for auditing and compliance. ## Demonstration with Claude Code - Without the MCP Server, Claude Opus 4.6 suggested several valid ways to store embeddings on S3 but missed Amazon S3 Vectors because the service launched after its training cutoff. - With the MCP Server, Claude Code searched current AWS documentation and correctly identified S3 Vectors. - Claude Code can connect through the open-source `mcp-proxy-for-aws`, which bridges local IAM credentials and MCP’s OAuth 2.1 requirement. - The server works with Claude Code, Kiro, Cursor, Codex, and other MCP-compatible clients. ## Availability and Cost - The service is available in US East (N. Virginia) and Europe (Frankfurt). - It can make API calls across AWS Regions. - There is no additional charge for the MCP Server; users pay for AWS resources and applicable data transfer. The AWS MCP Server is a practical foundation for giving agents current AWS knowledge and controlled operational access. Teams should pair it with narrowly scoped IAM policies, read-only defaults where possible, and CloudWatch or CloudTrail monitoring.
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