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AWS presents a centralized Model Context Protocol (MCP) server implementation using Amazon Bedrock for enterprise AI workloads. The solution addresses challenges of siloed tool development by providing a shared registry of MCP servers that teams can access across different lines of business. The architecture uses AWS ECS on Fargate for scalability, Network Load Balancer for access control, and private VPC endpoints for security. A financial services use case demonstrates post-trade execution workflows, showing how agents can discover and execute tools through the centralized MCP hub. The approach enables organizations to standardize AI tool access, reduce operational overhead, and accelerate AI agent development while maintaining enterprise governance and security requirements.

Accelerating AI innovation: Scale MCP servers for enterprise workloads with Amazon Bedrock

Agentic application interaction with a central MCP server hub