Authors: Igor Alekseev (PSA AWS) , Anuj Panchal (SA MongoDB) , Vin Dahake (SA AWS) AI agents are only as useful as the tools they can access. With the Model Context Protocol (MCP) becoming the standard for connecting AI models to external data sources, running MCP servers in managed cloud environments is the natural next step. In this post, we'll walk through deploying the MongoDB MCP Server on Amazon Bedrock AgentCore - giving your AI agents direct, structured access to MongoDB databases. What You're Building By the end of this guide, you'll have a containerized MongoDB MCP Server running as an AgentCore MCP runtime. Your AI agents will be able to query collections, inspect schemas, run aggregations, and interact with MongoDB Atlas - all through the MCP protocol, managed by AgentCore. The architecture is straightforward: AI Agent → Bedrock AgentCore → MongoDB MCP Server (container) → MongoDB / Atlas AgentCore handles session management, scaling, and invocation routing.…