5-Agent Orchestration System for n8n workflow automation with Claude Code.
ClaudeN8N is a complete multi-agent system that automates n8n workflow creation, debugging, and maintenance through a team of specialized AI agents working together.
Current Version: v3.7.0 (2025-12-15)
- Automates workflow building through 5-phase collaborative process
- Prevents critical incidents via protected nodes, surgical edits, and validation gates
- Preserves knowledge in structured ADRs, service playbooks, and learning database
- Optimizes token usage through agent-scoped indexes and file-based context
- Enforces safety via hooks that prevent hallucinated operations and accidental deletions
| Agent | Model | Role | Responsibility |
|---|---|---|---|
| Architect | Sonnet 4.5 | Planning & Dialog | Clarifies requirements, presents options, coordinates phases |
| Researcher | Sonnet 4.5 | Search & Discovery | Finds nodes, templates, credentials, and documentation |
| Builder | Opus 4.5 | Implementation | Creates/modifies workflows via surgical edits only |
| QA | Sonnet 4.5 | Validation & Testing | Validates changes, runs tests, enforces edit scope |
| Analyst | Sonnet 4.5 | Analysis & Documentation | Post-mortems, updates .context/ files, tracks tokens |
Orchestrator = Main context that routes between agents (not a separate agent file)
ClaudeN8N/
├── README.md # Project overview
├── CHANGELOG.md # Version history (v3.7.0)
├── CREDENTIALS.env # Local credentials (git-ignored)
├── .mcp.json # MCP server configuration
│
├── .claude/ # Claude Code configuration
│ ├── CLAUDE.md # System instructions (auto-loaded)
│ │
│ ├── commands/ # Slash commands
│ │ └── orch.md # Orchestrator (main entry point, ~5,765 tokens)
│ │
│ ├── agents/ # Agent specifications (~23,610 tokens total)
│ │ ├── architect.md # Planning agent (~1,700 tokens)
│ │ ├── researcher.md # Search agent (~3,800 tokens)
│ │ ├── builder.md # Implementation agent (~4,950 tokens)
│ │ ├── qa.md # Validation agent (~4,225 tokens)
│ │ ├── analyst.md # Analysis agent (~3,170 tokens)
│ │ └── shared/ # Shared protocols
│ │ ├── anti-hallucination.md # MCP checks (486 tokens)
│ │ ├── project-context.md # Reading order (463 tokens)
│ │ ├── surgical-edits.md # Partial updates (672 tokens)
│ │ └── context-update.md # Documentation sync (574 tokens)
│ │
│ └── hooks/ # Enforcement hooks
│ ├── block-full-update.md # PreToolUse: Force surgical edits
│ └── enforce-context-update.md # PostToolUse: Trigger Analyst
│
├── docs/
│ ├── INDEX.md # Documentation index
│ ├── ARCHITECTURE.md # System architecture (updated v3.7.0)
│ ├── WORKFLOWS.md # Workflow examples
│ │
│ └── learning/ # Knowledge base
│ ├── LEARNINGS.md # Problems & solutions (50+ entries)
│ ├── LEARNINGS-INDEX.md # Fast lookup index (98% token savings)
│ ├── PATTERNS.md # Proven patterns (15+ patterns)
│ └── N8N-RESOURCES.md # External resources
│
├── memory/ # Run state and agent results
│ ├── run_state_active.json # Current workflow (compacted, ~800 tokens)
│ ├── run_state_history/ # Per-workflow history
│ ├── run_state_archives/ # Completed workflows
│ ├── agent_results/ # Agent outputs (workflow-isolated)
│ └── workflow_snapshots/ # Version backups
│
└── {project_path}/.context/ # Project-specific documentation (NEW v3.7.0)
├── 1-STRATEGY.md # Mission, goals, boundaries
├── 2-INDEX.md # Navigation hub, protected nodes
├── architecture/
│ ├── flow.md # Data flow diagrams
│ ├── decisions/ # Architecture Decision Records (ADRs)
│ ├── services/ # Service playbooks (Telegram, Supabase)
│ └── nodes/ # Critical node intent cards
└── technical/
└── state.json # Current workflow state
-
Copy environment template:
cp .env.example CREDENTIALS.env
-
Edit
CREDENTIALS.envwith your n8n API credentials -
MCP server is pre-configured in
.mcp.json
| Document | Description |
|---|---|
| docs/INDEX.md | Full documentation index |
| docs/ARCHITECTURE.md | System architecture |
| docs/WORKFLOWS.md | Workflow patterns |
| Document | Description |
|---|---|
| LEARNINGS.md | Problems & solutions database |
| LEARNINGS-INDEX.md | Fast lookup index |
| PATTERNS.md | Proven solution patterns |
| N8N-RESOURCES.md | External n8n resources |
All workflow tasks must use the /orch command (enforced via hooks):
/orch Create a Telegram bot that tracks food intake
/orch Fix the webhook authentication issue
/orch Add rate limiting to the API workflowThe orchestrator automatically:
- Clarifies requirements via Architect ←→ User dialog
- Researches solutions via Researcher (nodes, templates, patterns)
- Presents options via Architect ←→ User decision
- Implements via Builder (surgical edits only)
- Validates via QA (max 7 cycles with progressive escalation)
- Documents via Analyst (.context/ updates, git commits)
User Request
↓
PHASE 1: CLARIFICATION → Architect ←→ User
↓
PHASE 2: RESEARCH → Researcher (search nodes, templates, credentials)
↓
PHASE 3: DECISION + CREDS → Architect ←→ User + Researcher (discover credentials)
↓
PHASE 4: IMPLEMENTATION → Researcher (deep dive: learnings, patterns, gotchas)
↓
PHASE 5: BUILD → Builder → QA → (fix loop) → complete | blocked
File-Based Context Protocol:
- Each project has
.context/directory with structured documentation - Agents read context directly instead of embedded JSON in Task calls
- ~10,000 tokens saved per workflow build
Protected Nodes & Surgical Edits:
- Projects document DO NOT TOUCH rules in
2-INDEX.md - Builder uses
n8n_update_partial_workflowonly (full updates blocked via hooks) - QA validates Builder only modified declared
edit_scope
Architecture Decision Records (ADRs):
- Critical decisions documented with incident history
- Service playbooks for Telegram, Supabase, etc.
- Node intent cards explain critical component purposes
Enforcement Hooks:
- PreToolUse: Block
n8n_update_full_workflow→ force surgical edits - PostToolUse: Trigger Analyst to update .context/ after Builder success
Token Optimization:
| Component | Tokens |
|---|---|
| Full system (5 agents + orchestrator) | ~23,610 |
| Active run state (compacted) | ~800 |
| Project .context/ (example: FoodTracker) | ~5,653 |
| Savings per workflow (vs embedded context) | ~10,000 |
| ROI after 10 workflows | 141× |
MIT