AWS Launches Serverless MCP Proxy on Bedrock AgentCore Runtime for Custom Agent Controls
AWS has released support for custom Model Context Protocol (MCP) proxies on Amazon Bedrock AgentCore Runtime, allowing organizations to implement custom governance and security controls on AI agent tool interactions without modifying upstream MCP servers. The serverless proxy runs on AgentCore Runtime with automatic scaling and built-in observability through CloudWatch and OpenTelemetry.
AWS Launches Serverless MCP Proxy on Bedrock AgentCore Runtime for Custom Agent Controls
Amazon Web Services has released support for custom Model Context Protocol (MCP) proxies on Amazon Bedrock AgentCore Runtime, enabling organizations to add programmable governance and security controls to AI agent tool interactions. The feature addresses production requirements including input sanitization, audit trail generation, and data redaction at the protocol layer.
How the MCP Proxy Works
The proxy runs as a serverless workload on AgentCore Runtime and acts as an intermediary between MCP clients and upstream MCP servers. At startup, the proxy sends a standard tools/list request to the upstream server to discover available tools, then dynamically registers local versions of each tool using FastMCP. Client requests flow through the proxy, which applies custom logic before forwarding to the upstream server.
The architecture consists of three layers: the MCP client, the MCP proxy on AgentCore Runtime, and the upstream MCP server. The upstream server can be hosted on AgentCore Runtime, self-hosted infrastructure, or third-party services. AWS recommends AgentCore Gateway as an upstream server for managed tool discovery, credential management, and policy enforcement.
Infrastructure and Authorization
AgentCore Runtime provides serverless infrastructure with automatic scaling, built-in observability through Amazon CloudWatch and OpenTelemetry, and AgentCore Identity for authentication and authorization. Authorization is enforced independently at each layer: agents authenticate to the proxy using AgentCore Identity, and the proxy authenticates to upstream servers as a standard MCP client.
The proxy implementation uses FastMCP to handle MCP protocol operations. Because the proxy is a standard Python MCP server, developers can insert custom logic before forwarding tool calls or after receiving responses, without replacing the upstream server's native capabilities.
Alternative to Lambda Interceptors
While Amazon Bedrock AgentCore Gateway supports Lambda interceptors for running validation and transformation code on every tool invocation, the MCP proxy pattern is designed for organizations with existing MCP filtering logic tightly coupled to internal libraries or on-premises compliance systems. The serverless proxy approach offers portability across multiple systems and hybrid environments without requiring refactoring into Lambda functions.
Availability
The feature is available now on Amazon Bedrock AgentCore Runtime. AWS has published an open source GitHub implementation to provide a foundation for deploying custom MCP proxies. Pricing follows standard AgentCore Runtime compute and CloudWatch observability costs.
What This Means
This release gives organizations running AI agents on AWS infrastructure a standardized way to implement custom protocol-layer controls without vendor lock-in to Lambda-specific implementations. The serverless proxy pattern is particularly relevant for enterprises migrating existing MCP governance systems to AWS or operating hybrid environments where tool access policies must be portable across multiple platforms. By supporting standard Python MCP servers rather than requiring AWS-specific handlers, the approach preserves code reusability while gaining the operational benefits of managed serverless infrastructure.
Related Articles
Amazon Reportedly Scales Back Nova AI Models, Shifts Resources to New Frontier Research Team
Amazon is reportedly scaling back active development of its Nova Premier, Nova Omni, Reel, and Canvas AI models, according to Business Insider. Resources are shifting to a new Frontier Model Research group led by Pieter Abbeel, with a new foundation model reportedly planned for re:Invent this fall.
Perplexity Brings Personal Computer AI Agent Tool to Windows
Perplexity has launched Personal Computer for Windows, extending its agentic AI tool beyond Mac to work directly across local files, Microsoft Office 365, and the web. The tool is rolling out now to Max and Enterprise Max subscribers on plans starting at $200 per month.
Guardoc Health Cuts Documentation Errors 46% Using Amazon Nova Models on Bedrock
Guardoc Health built a multi-stage document processing pipeline on Amazon Nova Pro, Nova Lite, and Titan Text Embeddings to extract and classify medical conditions from clinical PDFs at scale. The company claims a 46 percent reduction in documentation errors, 70 percent fewer audit fines, and over $400K in annual ROI for a single facility.
OpenAI Brings Agent-Controlling ChatGPT Voice Mode to Desktop App
OpenAI has brought ChatGPT Voice to its desktop app, letting users direct AI agents in ChatGPT Work and Codex through spoken commands. The feature, powered by OpenAI's new GPT-Live model family, can execute multi-step tasks like creating pull requests and debugging code.
Comments
Loading...