Extending MCP support for Amazon Bedrock AgentCore Gateway
📰 AWS Machine Learning
Learn how Amazon Bedrock AgentCore Gateway extends MCP support for secure and scalable model deployment
Action Steps
- Deploy Amazon Bedrock AgentCore Gateway between MCP servers and clients
- Configure fine-grained access control using the gateway
- Implement observability to track team tool usage
- Set up centralized credential management for secure authentication
- Test the integration for scalability and security guarantees
Who Needs to Know This
Machine learning engineers and DevOps teams can benefit from this integration to improve the security and scalability of their model deployments
Key Insight
💡 Centralizing credential management and observability with Amazon Bedrock AgentCore Gateway improves the security and scalability of MCP server deployments
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🚀 Extend MCP support with Amazon Bedrock AgentCore Gateway for secure & scalable model deployment!
Key Takeaways
Learn how Amazon Bedrock AgentCore Gateway extends MCP support for secure and scalable model deployment
Full Article
While deploying Model Context Protocol (MCP) servers in production, enterprises need fine-grained access control across servers, observability into which teams use which tools, security guarantees against data exfiltration, and centralized credential management, all at scale. Amazon Bedrock AgentCore Gateway sits between MCP servers and the clients that consume them, centralizing credential management, observability, and secure […]
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