AgentFlow is a visual platform that makes multi-agent AI orchestration accessible to everyone. Design agent workflows using an intuitive org-chart interfaceβno coding required.
Companies struggle to coordinate multiple AI agents for complex workflows. Traditional solutions require:
- Complex code and technical expertise
- Manual orchestration between agents
- Difficult-to-visualize agent hierarchies
- Time-consuming setup and iteration
AgentFlow provides a visual, drag-and-drop interface where users can:
- Create agents with custom instructions (like employees in an org chart)
- Define hierarchies by drawing arrows between agents
- Execute workflows by passing data through the visual pipeline
- See results in real-time with visual feedback
- π¨ Visual Canvas - Drag-and-drop agent creation and positioning
- π Connection System - Draw arrows to define agent hierarchy
- π€ Claude Integration - Each agent powered by Claude 3.5 Sonnet
- β‘ Real-time Execution - Watch your workflow execute step-by-step
- π Visual Feedback - Active agent highlighting and status indicators
- Intake Agents - Receive and categorize initial requests
- Processing Agents - Perform main tasks and transformations
- Response Agents - Format and deliver final outputs
- π Customer Support Workflow - Automated ticket triage and resolution
- More templates coming soon
- Node.js 18+ installed
- An Anthropic API key (get one here)
-
Clone the repository
git clone https://github.com/yourusername/agentflow.git cd agentflow -
Install dependencies
npm install
-
Configure environment variables
cp .env.example .env.local
Edit
.env.localand add your Anthropic API key:ANTHROPIC_API_KEY=your_api_key_here -
Run the development server
npm run dev
-
Open your browser Navigate to http://localhost:3000
- Load a Template - Click "π Load Template" to see an example workflow
- Add Input - Enter a test query in the Execution Panel
- Run Workflow - Click "
βΆοΈ Run Workflow" to see it in action
-
Create Agents
- Click "+ Create Agent"
- Give it a name (e.g., "Email Classifier")
- Choose agent type (Intake, Processing, or Response)
- Write instructions for what the agent should do
-
Connect Agents
- Drag from the right handle of one agent to the left handle of another
- This defines the flow direction
-
Test Your Workflow
- Enter a test input in the Execution Panel
- Click "Run Workflow"
- Watch as each agent processes the data in sequence
- Frontend: Next.js 16 + React + TypeScript
- UI Components: React Flow (visual canvas), Tailwind CSS
- State Management: Zustand
- AI Integration: Anthropic Claude 3.5 Sonnet API
- Deployment: Vercel
app/
βββ api/execute/ # API endpoint for workflow execution
βββ layout.tsx # Root layout with metadata
βββ page.tsx # Main application page
components/
βββ FlowCanvas.tsx # React Flow canvas container
βββ AgentNode.tsx # Custom node component for agents
βββ AgentModal.tsx # Agent creation/editing modal
βββ ExecutionPanel.tsx # Workflow execution interface
store/
βββ useFlowStore.ts # Zustand state management
types/
βββ index.ts # TypeScript type definitions
- User Input β Enters query in Execution Panel
- Topological Sort β Determines agent execution order based on connections
- Sequential Processing β Each agent:
- Receives context from previous agent (or initial input)
- Calls Claude API with its specific instructions
- Returns output to next agent
- Real-time Updates β UI shows active agent and results as they come in
- Final Output β Last agent's response shown to user
- Intake Agent: Categorizes tickets (billing, technical, general)
- Processing Agent: Provides solutions or escalation recommendations
- Response Agent: Formats empathetic customer-facing response
- Intake Agent: Analyzes new hire information
- Processing Agent: Generates onboarding checklist
- Response Agent: Creates welcome email
- Intake Agent: Extracts lead information
- Processing Agent: Scores and qualifies lead
- Response Agent: Generates personalized outreach
- β Reduces agent setup time from hours to minutes
- β Makes AI workflows accessible to non-technical teams
- β Solves real coordination challenges companies face
- β First visual org-chart interface for AI agents
- β Intuitive business metaphor (employees β agents)
- β Makes complex AI orchestration simple
- β Multi-agent architecture powered by Claude 3.5 Sonnet
- β Each agent maintains context through conversation
- β Demonstrates Claude's versatility across different roles
-
Push to GitHub
git add . git commit -m "Initial commit" git push origin main
-
Deploy to Vercel
- Go to vercel.com
- Import your GitHub repository
- Add environment variable:
ANTHROPIC_API_KEY - Click "Deploy"
-
Done! Your app is now live
We welcome contributions! Here's how:
- Fork the repository
- Create a feature branch (
git checkout -b feature/amazing-feature) - Commit your changes (
git commit -m 'Add amazing feature') - Push to the branch (
git push origin feature/amazing-feature) - Open a Pull Request
This project is built for the Claude Builder Club x ACT Rice Hackathon (Nov 8-9, 2025).
- Anthropic - For Claude AI and the hackathon opportunity
- React Flow - For the excellent flowchart library
- Vercel - For seamless deployment
Built with β€οΈ for the Claude Builder Club Hackathon
Made with Claude AI π€