Jarvis Integration with AWS AgentCore
This video demonstrates how Jarvis integrates with AWS Agent Core to enable non-technical users to query databases using natural language. Traditionally, teams had to manage Docker builds, cloud configurations, and complex security settings to deploy AI capabilities. With Amazon Bedrock Agent Core, a managed AWS service, those steps are replaced by a single command, dramatically lowering the barrier to deploying MCP servers at scale.
The deployment workflow starts with agent core configure, a guided prompt that collects your MCP server entry point, IAM role, and ECR repository — or lets AWS create them automatically. Running agent core launch then builds the Docker container, pushes it to Amazon ECR, creates the Bedrock Agent Core runtime, and deploys the server to AWS. Teams can then access an observability dashboard and CloudWatch logs directly in the AWS console.
After continuous iteration using Agent Core automation, the team achieved over 95% accuracy in natural language query translation. The video shows healthcare use cases where compliance and finance teams can instantly query physician payment records, and social media specialists can assess engagement metrics and generate shareable visual reports — all without writing SQL or managing infrastructure.
Non-technical team members struggle to access and query databases. Traditional approaches required managing Docker builds, cloud configurations, and complex security settings, making AI deployment slow and innovation difficult.
AWS Agent Core is a managed service that automates the full AI deployment process. Jarvis uses it to deploy a DynamoDB MCP server, replacing previously complex infrastructure steps with a single command.
The agent core configure command runs a guided workflow to supply the MCP server entry point, IAM role, and ECR repo — AWS creates any skipped resources automatically. Running agent core launch then builds the Docker image, pushes it to ECR, and deploys the Bedrock Agent Core runtime.
After deployment, teams access the Agent Core page in the AWS console for an observability dashboard, CloudWatch logs, and runtime configuration updates. Continuous iteration achieved over 95% accuracy in natural language query translation.
A compliance or finance team member can ask Jarvis to generate a ranked list of physicians by payment amount and view all payment details instantly, strengthening compliance and transparency without requiring SQL expertise.
A social media specialist can ask Jarvis to assess engagement metrics across physician tweets, identify top-performing campaigns, and generate interactive charts and shareable reports — all through natural language powered by Agent Core.
