Visual multi-agent AI orchestration platform. Design, execute, and monitor complex AI pipelines using a drag-and-drop canvas — no config files, no infrastructure.
AgentFlow lets you build multi-agent AI workflows visually. Each node is a Claude-powered agent with its own role, system prompt, and parameters. Connect agents to pass outputs downstream, run the whole pipeline with a single prompt, and watch each agent execute in real-time.
Built on top of Claude (claude-sonnet-4-20250514) via the Anthropic API.
- Visual Pipeline Canvas — Drag-and-drop React Flow canvas. Connect agents into sequential or parallel pipelines. Live status indicators on every node.
- Multi-Agent Execution Engine — DAG-based execution with Kahn's topological sort. Parallel agents run concurrently via
Promise.all. Context from predecessor agents is automatically passed downstream. - Real-Time Streaming — SSE-powered live output. Watch each agent generate tokens as they arrive, not when they finish.
- 4 Built-in Templates — Deep Research, Code Review (4-agent parallel), Content Creation, and Competitive Analysis pipelines ready to run immediately.
- Pipeline Library — Browse templates by category, load them to canvas in one click.
- Analytics Dashboard — Run history, success rates, token usage, 30-day activity chart.
- Import / Export — JSON pipeline definitions you can version-control, share, and modify programmatically.
- REST API — Full programmatic access. Run pipelines, retrieve results, integrate with your own tools.
- Full Test Suite — Integration tests for all API routes. Unit tests for the orchestration engine with a mocked Claude client. No API key required to run tests.
- CI/CD — GitHub Actions pipeline: type-check, test, build.
agentflow/
├── apps/
│ ├── api/ Express + TypeScript backend
│ │ └── src/
│ │ ├── services/orchestration.ts DAG execution engine
│ │ ├── services/claude.ts Anthropic SDK wrapper
│ │ ├── services/sse.ts Real-time streaming
│ │ ├── models/ SQLite data access
│ │ └── routes/ REST endpoints
│ └── web/ React + TypeScript frontend
│ └── src/
│ ├── components/Canvas/ React Flow canvas
│ ├── components/Execution/ Live streaming panel
│ ├── components/Library/ Template browser
│ ├── components/Dashboard/ Metrics + history
│ └── store/ Zustand global state
├── tests/api/ Integration + unit tests
├── docs/ Architecture + API reference
└── .github/ CI workflows
The execution engine uses Kahn's BFS algorithm for topological ordering. Nodes whose predecessors have all completed execute concurrently. A 4-agent fan-in pipeline runs the 3 parallel agents simultaneously, then the coordinator receives all their outputs at once.
See docs/architecture.md for the full system diagram and design decisions.
- Node.js ≥ 18
- An Anthropic API key (get one here)
git clone https://github.com/yourusername/agentflow.git
cd agentflow
npm installcp .env.example .env
# Add your Anthropic API key to .envnpm run devThis starts both the API (port 3001) and the React frontend (port 5173). Open http://localhost:5173.
- Click Library in the sidebar
- Load the Deep Research Pipeline template
- Go back to Canvas
- Click Run and enter a research topic
- Watch three agents execute in real-time in the execution panel
| Template | Agents | Pattern | Best for |
|---|---|---|---|
| Deep Research | 3 | Sequential | Comprehensive research reports |
| Code Review | 4 | Parallel fan-in | Multi-perspective code reviews |
| Content Creation | 3 | Sequential | Blog posts, articles, copy |
| Competitive Analysis | 2 | Sequential | Market research, strategy |
npm run test # All tests
npm run test:api # API integration + unit tests only
npm run test:web # Frontend component tests onlyTests use an in-memory SQLite database and a mocked Claude client — no API key required.
# List pipelines
GET /api/pipelines
# Create a pipeline
POST /api/pipelines
{ "name": "My Pipeline", "nodes": [...], "edges": [...] }
# Run a pipeline (sync)
POST /api/executions/run-sync
{ "pipelineId": "uuid", "input": "Your prompt here" }
# Dashboard metrics
GET /api/executions/metricsSee docs/api-reference.md for the full spec.
| Layer | Tech |
|---|---|
| Frontend | React 18, TypeScript, Vite, React Flow, Zustand, Lucide |
| Backend | Node.js, Express, TypeScript |
| Database | SQLite (better-sqlite3), WAL mode |
| AI | Claude API via @anthropic-ai/sdk |
| Real-Time | Server-Sent Events |
| Testing | Jest, Supertest, Vitest, React Testing Library |
| CI/CD | GitHub Actions |
| Package Management | npm workspaces (monorepo) |
MIT