aws-ai-agent-bus

Baur-Software/aws-ai-agent-bus

3.4

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The Model Context Protocol (MCP) server is a production-ready server designed to facilitate AI assistant integration with AWS services through standardized interfaces.

AI Agent Bus

Multi-tenant business process automation platform with live workflow execution, human-in-the-loop operations, and AI-powered agent generation.

An intelligent workflow platform that combines automated processes with human decision points, featuring real-time execution monitoring and automatic integration discovery through MCP servers.

What This Project Includes

A comprehensive workflow automation platform:

  • Live Workflow Registry: Real-time execution state with visual node updates
  • Human-in-the-Loop Nodes: People as first-class workflow participants with smart notifications
  • Auto-Generated AI Agents: Automatic specialist agent creation from connected MCP servers
  • Multi-Tenant Agent Storage: Organization and user-scoped agent management with S3/IAM security
  • Integration Discovery: Connect apps and auto-populate workflow capabilities
  • Visual Canvas: Drag-and-drop interface for designing mixed human/automated processes

Current Capabilities:

  • Multi-Tenant Agent System: Organization and user-scoped AI agents with S3 path-based security
  • Live Workflow Execution: Real-time node state updates via event streams
  • Human Workflow Nodes: People as workflow participants with customizable notification preferences
  • MCP Integration Discovery: Auto-populate workflow nodes from connected MCP servers
  • Specialist Agent Auto-Generation: Create specialized agents from MCP server capabilities
  • Visual Canvas Design: Drag-and-drop interface for mixed human/automated processes
  • Versioned Agent Storage: Full CRUD operations with S3 versioning and DynamoDB metadata

Architecture

Core Components

  • Dashboard UI (SolidJS): Visual workflow designer with live execution monitoring
  • Dashboard Server (Node.js): WebSocket-based pub/sub backend with multi-tenant agent management
  • MCP Server (Node.js): Model Context Protocol server providing AI context and tool execution
  • Internal MCP Registry: Versioned registry of connected MCP servers with fork support
  • Multi-Tenant Agent Storage: S3/DynamoDB-backed agent system with path-based security
  • Live Workflow Engine: Real-time execution state management with event streaming
  • Human Notification System: Multi-channel notifications (Slack, email, SMS) for human workflow nodes

Data Architecture

Agent Storage:

S3: agents/
ā”œā”€ā”€ public/system/              # Bootstrap agents from .claude/agents
ā”œā”€ā”€ public/community/           # Community-shared agents
ā”œā”€ā”€ organizations/{orgId}/
ā”‚   ā”œā”€ā”€ shared/                # Org-wide agents
ā”‚   ā”œā”€ā”€ generated/{mcpId}/     # Auto-generated from MCP servers
ā”‚   ā””ā”€ā”€ users/{userId}/        # User private agents within org
ā””ā”€ā”€ users/{userId}/            # Individual user agents

Multi-Tenant Context:

  • Organizations: Multiple users, shared resources, admin controls
  • Users: Individual workspaces, private agents, personal integrations
  • MCP Tenant Isolation: Each user/org has isolated MCP server context

Technical Stack

  • Frontend: SolidJS with TypeScript
  • Backend: Node.js MCP server with stdio/HTTP interfaces
  • Infrastructure: AWS (DynamoDB, S3, EventBridge, Step Functions)
  • AI Integration: OpenAI/Claude via MCP protocol

Quick Start

1. Clone and Setup

git clone https://github.com/your-org/aws-ai-agent-bus
cd aws-ai-agent-bus

# Start the dashboard UI
cd dashboard-ui
npm install
npm run dev

# Start the MCP server (separate terminal)
cd ../mcp-server
npm install
npm start

2. Try the Interface

Open http://localhost:5173 to access:

  1. Visual Canvas: Design workflows with drag-and-drop
  2. Business Templates: Pre-built process flows
  3. Chat Assistant: Get AI suggestions (currently mock responses)
  4. Process Library: Browse and manage your workflows

3. Deploy Infrastructure (Optional)

# Deploy AWS components for MCP server
export WS=small/kv_store ENV=dev
npm run tf:init
npm run tf:apply

Use Cases

Human-in-the-Loop Operations

Financial Approval Workflows:

API Request ā†’ Data Validation ā†’ Human Approval ā†’ Payment Processing ā†’ Notification
    šŸ¤–             šŸ¤–               šŸ‘¤                šŸ¤–               šŸ¤–
  • Finance manager gets Slack notification for payments >$10k
  • Mobile-friendly approval with full context
  • Automatic escalation if no response within 2 hours

Customer Onboarding with Review:

Form Submission ā†’ Data Enrichment ā†’ Compliance Check ā†’ Manual Review ā†’ Account Creation
      šŸ¤–               šŸ¤–               šŸ¤–             šŸ‘¤              šŸ¤–
  • Compliance officer reviews flagged applications
  • Customizable notification preferences per person
  • Real-time workflow state visible to all stakeholders

Auto-Generated Integration Workflows

Connect Stripe ā†’ Instant Specialized Agents:

  1. User connects Stripe MCP server to tenant context
  2. System auto-generates: stripe-payments-expert, stripe-webhooks-specialist, stripe-subscriptions-manager
  3. Workflow nodes populate with Stripe capabilities
  4. Pre-built payment processing workflows become available

GitHub Integration ā†’ Development Workflows:

  1. Connect GitHub MCP server
  2. Auto-generate: github-pr-manager, github-deployment-specialist, github-issue-tracker
  3. CI/CD workflow templates with human review gates
  4. Automatic agent updates when MCP server versions change

Multi-Tenant Agent Management

Organization-Level Sharing:

  • acme-corp creates custom salesforce-lead-qualifier agent
  • Available to all acme-corp users in workflow designer
  • Version controlled with change logs

Personal Agent Development:

  • Individual users create private specialized agents
  • Fork organization agents for personal customization
  • Markdown editor with live preview and templates

Project Status

āœ… Implemented:

  • Multi-Tenant Agent Storage: S3/DynamoDB with path-based security and versioning
  • Agent CRUD Operations: Full create, read, update, delete with AWS SDK integration
  • S3 Security Architecture: IAM policies supporting user/org/public agent isolation
  • Frontmatter Parsing: Markdown agent definitions with YAML metadata extraction
  • Version Management: Automatic versioning for agent updates with changelog support

šŸš§ In Development:

  • Feature Flag Authentication: Dev user injection (user-demo-123/acme) for immediate testing
  • WebSocket Agent Operations: Pub/sub message handlers for real-time agent management
  • Internal MCP Registry: Versioned registry with fork support and tenant context
  • Auto-Agent Generation: Specialist agent creation from connected MCP server capabilities
  • Live Workflow Execution: Real-time node state updates with event streaming
  • Human Workflow Nodes: People as workflow participants with smart notifications

šŸŽÆ Planned:

  • Markdown Agent Editor: Universal editor with templates, live preview, syntax highlighting
  • MCP Server Discovery: Integration with mcpservers.org for app connection workflows
  • Mobile Notifications: Multi-channel human node notifications (Slack, SMS, email)
  • Production Authentication: AWS Cognito integration with JWT-based user context
  • Workflow Marketplace: Published workflow sharing and discovery

Contributing

See for development guidelines and setup instructions.

Documentation

  • - Complete codebase overview and architecture
  • - MCP server documentation
  • - Agent orchestration system
  • - Terraform infrastructure modules

Contributing

See for development guidelines.

License

MIT License - see for details.