MVP Overview

Vision & Objectives

The Agent Party MVP aims to create a functional foundation for AI agent collaboration through a distributed, event-driven architecture. This specification outlines the integration of Kafka, Neo4j, MinIO, and Redis to create a scalable and resilient platform.

Core MVP Functionality

  • Agent registration and discovery
  • Event-based communication between agents
  • Persistent storage of agent knowledge and artifacts
  • Graph-based relationship modeling between agents and resources
  • Caching of frequently accessed data for performance optimization

Success Criteria

  • Successful registration of at least 3 different agent types
  • Verified end-to-end communication between agents
  • Successful storage and retrieval of artifacts
  • Demonstrated relationship queries in the graph database
  • All tests passing with acceptable performance metrics
Kafka Neo4j MinIO Redis Agent Party Core Events Relations Artifacts Cache Agent 1 Agent 2 Agent 3

System Architecture

High-Level Architecture Diagram

Agent Layer Doorman Agent DJ Agent Bartender Agent Messaging Layer Kafka Event Bus Topics: agent.events, agent.requests, agent.responses Core Layer Agent Registry Neo4j + Redis Event Processor Kafka Streams State Manager Redis Storage Layer Graph DB (Neo4j) Object Storage (MinIO) Cache (Redis)

Component Responsibilities

Component Responsibility
Kafka Event bus for all agent communication, providing message queuing, event streaming, and topic-based message routing
Neo4j Graph database for storing agent relationships, capabilities, and interaction patterns
MinIO Object storage for artifacts, file attachments, and binary data generated or consumed by agents
Redis In-memory data store for caching frequently accessed data, session management, and real-time state

Technical Constraints

Performance Requirements
  • Message delivery latency < 500ms
  • Agent registration time < 2 seconds
  • Graph query response time < 1 second
  • System must handle at least 50 concurrent agent connections
Scalability Considerations
  • Horizontal scaling of Kafka brokers
  • Neo4j clustering for graph data
  • MinIO distributed deployment
  • Redis cluster for cache distribution

Agent Party MVP Specification © 2025