Component Specification

This document details the core components of the Agent Party MVP, their interfaces, and how they integrate to form a cohesive system.

Kafka: Event Messaging System

Core Functionality

Kafka serves as the central nervous system of the Agent Party platform, handling all event-based communication between agents and system components.

Responsibilities

  • Provide reliable message delivery with exactly-once semantics
  • Enable real-time event streaming between components
  • Support topic-based message routing
  • Maintain message ordering within partitions
  • Provide message persistence with configurable retention

Topic Structure

Topic Purpose Partitions
agent.registration Agent registration events 4
agent.events General purpose agent events 8
agent.requests Service requests from agents 8
agent.responses Service responses to agents 8
system.logs System logging and monitoring 4

Implementation Details

Configuration

  • 3 broker cluster for fault tolerance
  • Zookeeper ensemble for coordination
  • Replication factor: 3
  • Min in-sync replicas: 2
  • Default retention: 7 days

Producer Configuration

bootstrap.servers=kafka:9092
acks=all
retries=10
batch.size=16384
linger.ms=5
key.serializer=org.apache.kafka.common.serialization.StringSerializer
value.serializer=io.confluent.kafka.serializers.KafkaAvroSerializer
schema.registry.url=http://schema-registry:8081

Consumer Configuration

bootstrap.servers=kafka:9092
group.id=agent-party-service
enable.auto.commit=false
auto.offset.reset=earliest
key.deserializer=org.apache.kafka.common.serialization.StringDeserializer
value.deserializer=io.confluent.kafka.serializers.KafkaAvroDeserializer
schema.registry.url=http://schema-registry:8081

Integration Points

  • All agents connect as producers and consumers
  • System services use Kafka Streams for event processing
  • Schema Registry ensures schema compatibility
  • Agent Registry consumes registration events

Neo4j: Graph Database

Core Functionality

Neo4j provides the graph database infrastructure for modeling agent relationships, capabilities, and interaction patterns.

Responsibilities

  • Store agent profiles and metadata
  • Model relationships between agents
  • Track agent capabilities and services
  • Support graph queries for agent discovery
  • Maintain interaction history between agents

Node Types

Node Label Purpose Key Properties
Agent Represents an agent in the system id, name, type, status
Capability Represents a capability an agent can provide id, name, description
Resource External resource an agent can access id, type, location
Event Represents a significant system event id, type, timestamp

Relationship Types

Relationship Purpose
:HAS_CAPABILITY Links an Agent to a Capability it provides
:DEPENDS_ON Indicates an Agent depends on another Agent
:ACCESSES Links an Agent to Resources it can access
:PARTICIPATED_IN Links an Agent to Events it participated in

Implementation Details

Configuration

  • Single node setup for MVP (clustered in production)
  • Authentication enabled
  • HTTPS for encrypted communication
  • Regular backup schedule

Sample Cypher Queries

Register New Agent
CREATE (a:Agent {
  id: $agentId,
  name: $name,
  type: $type,
  status: 'ACTIVE',
  created: datetime()
})
RETURN a
Find Agents by Capability
MATCH (a:Agent)-[:HAS_CAPABILITY]->(c:Capability)
WHERE c.name = $capabilityName
RETURN a.id, a.name, a.type
Find Path Between Agents
MATCH path = shortestPath(
  (a:Agent {id: $sourceId})-[*]-(b:Agent {id: $targetId})
)
RETURN path

Integration Points

  • Agent Registry service interfaces with Neo4j
  • Event Processor updates relationship data
  • Redis caches frequent graph queries
  • GraphQL API exposes graph data to agents

MinIO: Object Storage

Core Functionality

MinIO provides S3-compatible object storage for artifacts, file attachments, and binary data generated or consumed by agents.

Responsibilities

  • Store binary artifacts and file objects
  • Provide secure access to stored objects
  • Support object versioning and lifecycle policies
  • Enable efficient object retrieval by unique IDs
  • Support metadata tagging for objects

Bucket Structure

Bucket Purpose Access Pattern
agent-resources Resources provided by or for agents Read-heavy
agent-artifacts Artifacts generated by agent interactions Write-then-read
system-logs System logging data Write-heavy
temp-storage Temporary object storage with expiration Mixed, short-lived

Implementation Details

Configuration

  • 4-node distributed setup
  • Erasure coding for data protection
  • TLS encryption for data in transit
  • Object locking for compliance
  • IAM policies for access control

Object Naming Convention

/{agent-id}/{object-type}/{uuid}

Required Metadata

Metadata Field Description
agent-id ID of the agent that owns or created the object
content-type MIME type of the stored object
created-at Timestamp when the object was created
source-event Event ID that triggered object creation (if applicable)

Integration Points

  • REST API for direct object operations
  • Presigned URLs for secure, time-limited access
  • Event notifications to Kafka on object changes
  • Neo4j stores object references, not the objects themselves

Redis: Caching & Real-time State

Core Functionality

Redis provides in-memory data storage for caching, session management, real-time state tracking, and high-speed lookups.

Responsibilities

  • Cache frequently accessed data from Neo4j
  • Maintain real-time agent status
  • Support distributed locking for concurrency control
  • Enable temporary storage of session data
  • Provide pub/sub capabilities for live updates

Data Structures

Data Type Use Case Key Pattern
Hash Agent profiles and metadata agent:{id}
Set Agent capabilities agent:{id}:capabilities
Sorted Set Agent ranking by activity agents:activity
List Recent events per agent agent:{id}:recent-events
String Configuration values config:{key}

Implementation Details

Configuration

  • Redis Sentinel for high availability
  • Password authentication
  • Snapshotting + AOF for persistence
  • Memory limit with LRU eviction
  • Keyspace notifications enabled

Cache Expiration Strategy

Data Category TTL Invalidation Strategy
Agent Profiles 30 minutes Active invalidation on update
Capability Data 1 hour Active invalidation on update
Session Data 15 minutes TTL-based expiration with refresh
Configuration 12 hours Active invalidation on update

Pub/Sub Channels

agent-status         # Agent status changes
agent-events         # Notable agent events
system-notifications # System-wide notifications

Integration Points

  • Agent Registry uses Redis for fast lookups
  • Neo4j query results cached in Redis
  • Event Processor publishes updates to Redis channels
  • System services use Redis for distributed locking

Agent Party MVP Specification © 2025