Multi-Agent System
The future of business automation: Agent-to-Agent (A2A) coordination where specialized agents collaborate to complete complex workflows. Coordination agents orchestrate task agents with different MCP integrations and capabilities.
Architecture
Multi-Agent A2A Coordination
┌─────────────────┐ A2A ┌──────────────┐
│ Producer Agent │ ◄─────────► │ Research │
│ (Coordinator) │ │ Agent │
└─────────┬───────┘ └──────────────┘
│ A2A │ MCP
▼ ▼
┌─────────────────┐ ┌──────────────┐
│ Design Agent │ │ Web APIs │
└─────────┬───────┘ │ Knowledge │
│ A2A │ Databases │
▼ └──────────────┘
┌─────────────────┐ MCP ┌──────────────┐
│ Animation Agent │ ◄─────────► │ Creative │
└─────────────────┘ │ Tools │
└──────────────┘A2A Capabilities
- • Cross-agent task coordination
- • Workflow orchestration and dependencies
- • Real-time status synchronization
- • Resource allocation and scheduling
- • Model-agnostic agent communication
Future Vision
Companies will have agent representatives capable of engaging with users and other company agents directly. Your scheduling agent books meetings, while a producer agent coordinates research, design, and animation via specialized task agents with different MCP integrations.
Live A2A Demo
Watch agents coordinate a complex creative project workflow
This demo shows how a Producer Agent coordinates with specialized task agents to complete a complex creative project using A2A communication.
Real Implementation
Coordination Agents
- • Workflow orchestration and planning
- • Resource allocation and scheduling
- • Cross-agent communication protocols
- • Dependency management and tracking
- • Performance monitoring and optimization
Task Agents
- • Specialized MCP tool integrations
- • Domain-specific capabilities
- • Independent task execution
- • Status reporting to coordinators
- • Model-agnostic implementations
A2A Communication
- • Inter-agent messaging protocols
- • Shared context and memory
- • Collaborative decision making
- • Scalable agent networks
- • Cross-company agent interaction
Real-World Example
Cadderly: Multi-Agent Knowledge System
See this architecture in action with our knowledge management platform
Cadderly demonstrates multi-agent coordination in production. Multiple specialized agents work together to index, process, and serve institutional knowledge across organizations.
Agent Coordination
- • Ingestion agents process documents
- • Analysis agents extract insights
- • Query agents serve information
- • Coordination agent orchestrates workflow
MCP Integrations
- • Slack, Teams, Discord
- • Google Drive, SharePoint
- • Notion, Confluence
- • Custom knowledge bases
The Agent Economy Future
Company Agent Representatives
Every company will have agent representatives capable of:
- • Engaging with customers autonomously
- • Negotiating with other company agents
- • Managing internal workflows and processes
- • Coordinating cross-company collaborations
Inter-Company A2A
Agent-to-agent business interactions will enable:
- • Automated vendor negotiations
- • Real-time supply chain coordination
- • Instant partnership agreements
- • Seamless service integrations
Ready to build your multi-agent system?
Design and implement custom multi-agent architectures with A2A coordination, MCP integrations, and scalable agent networks for your business workflows.