Workflow Patterns

Workflow Patterns

What do 7,698 real-world automation workflows have in common?
This project extracts the universal patterns — and turns them into explorable blueprints.

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This project parses 7,698 n8n workflow JSONs, maps 80+ node types to 9 abstract categories, and extracts the recurring patterns behind everyday automation. The result: an interactive explorer with blueprints for 12 use cases, and an MCP server that lets Claude Code query the pattern database directly.

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Live Explorer

Workflow Patterns Explorer

The Idea

People build automation workflows every day — in n8n, Make, Zapier, or with code. The tools differ, but the patterns are universal:

trigger -> ai -> deliver        (AI writes content, sends it somewhere)
trigger -> transform -> data    (data arrives, gets cleaned, gets stored)
trigger -> api -> logic -> api  (two systems talk to each other)

These patterns repeat across thousands of workflows. If you know the pattern, you know the architecture — regardless of which tools you use.

This project extracts those patterns from real data and makes them actionable.

Quick Start

git clone https://github.com/janrummel/workflow-patterns
cd workflow-patterns
uv sync

# Generate the interactive site
uv run python scripts/generate_site.py
open docs/index.html

# Or use as MCP server with Claude Code
claude --mcp-config mcp.json

Note: Adjust the cwd path in mcp.json to your local checkout location first.

Key Findings

Insight	Detail
7,698 workflows analyzed	From the n8nworkflows.xyz public archive
2,592 unique patterns	Distinct category sequences found across all workflows
12 use case clusters	AI Chatbot, Content Creation, Data Pipeline, Email Automation, and more
Most common pattern	trigger -> transform -> api -> logic (187 workflows)
AI is mainstream	45%+ of workflows include at least one AI node
Most workflows are small	4-6 nodes is the sweet spot — you don't need 20 steps

Interactive Explorer

The site lets you pick a use case and instantly get a complete blueprint:

• The pattern as an abstract step sequence
• Building blocks needed to implement it
• Tools & services grouped by category — showing alternatives, not just the most popular
• Starter code in Python with syntax highlighting
• Claude Code architecture recommendation

Blueprint View

View locally

Generate the interactive site and open it in your browser:

uv run python scripts/generate_site.py
open docs/index.html

How It Works

n8n JSON files (7,698 workflows)
    |
    v  parse
Workflow objects (nodes + edges)
    |  handles inconsistent JSON formats: null connections,
    |  string-wrapped lists, missing fields
    v  categorize
Abstract graphs (80+ node types -> 9 categories)
    |  "lmChatOpenAi" -> ai
    |  "googleSheets"  -> data
    |  "gmail"         -> deliver
    v  analyze
Patterns, statistics, use case clusters
    |  BFS graph traversal for pattern extraction
    |  Jaccard similarity for workflow matching
    v  translate
Claude Code architectures
    |  pattern -> MCP servers + agents + scripts
    v  serve
Interactive site  +  MCP server for Claude Code

The 9 Categories

Every node type maps to one abstract category. This is what makes patterns universal — the specific tool doesn't matter, only its role in the workflow.

Category	What it represents	Example nodes	Claude Code equivalent
trigger	Starts the workflow	scheduleTrigger, webhook, formTrigger	Cron job, file watcher
ai	LLM processing	openAi, lmChatOpenAi, agent	Claude agent
transform	Reshape data	set, code, filter, aggregate	Python script
deliver	Send output	gmail, slack, telegram	MCP server
data	Read/write storage	googleSheets, postgres, airtable	MCP server
api	Call external APIs	httpRequest	MCP server
logic	Branch, route, merge	if, switch, merge	Claude skill
storage	File operations	googleDrive, s3	MCP server

MCP Server

The project includes an MCP server that exposes pattern analysis to Claude Code. Connect it and ask natural language questions about automation patterns.

claude --mcp-config mcp.json

Then ask Claude:

"I want to build a workflow that fetches news articles weekly, summarizes them with AI, and sends a digest by email."

Claude will search the pattern database, find matching workflows, and suggest an architecture:

**Query:** Send a weekly AI summary of news articles by email
**Detected categories:** trigger, ai, deliver

**Matching workflows:**
- [80% match] Weekly AI Newsletter
  Pattern: trigger -> ai -> transform -> deliver
- [60% match] RSS Digest Bot
  Pattern: trigger -> api -> ai -> deliver

**Suggested pattern:** trigger -> ai -> deliver

Tool	What it does
search_patterns(query)	Find patterns matching a natural language description
suggest_implementation(pattern)	Get Claude Code architecture for a pattern
list_categories()	Show category frequency and common connections
show_all_patterns()	List all unique patterns ranked by frequency

Runnable Examples

Each example implements a real workflow pattern with current tools — not just a blueprint, but working code you can run.

Example	Pattern	What it does
AI Content Creation	api → ai → transform → deliver	Fetches RSS feeds, summarizes with Claude, saves a markdown digest
AI Chatbot	trigger → ai → data → deliver	Streaming terminal chat with 5 persona presets and conversation persistence
Email Automation	trigger → transform → deliver	Template-based emails with 5 presets, HTML rendering, and optional SMTP delivery
Scheduled Notifications	trigger → api → logic → deliver	Rule-based notification system with urgency levels and digest output
Data Pipeline	trigger → data → transform → data	Data processing with filter, aggregate, sort, rename, deduplicate transforms
API Integration	trigger → api → transform → data	REST API data collector with JSON path extraction and sample fallback

cd examples/ai-content-creation
uv sync
cp .env.example .env          # add your ANTHROPIC_API_KEY
uv run python run.py           # interactive feed selection
uv run python run.py --feeds https://hnrss.org/newest?points=100  # or custom

More examples coming: Form/Webhook Handler, Social Media Automation, and more.

Development

uv run pytest -v          # 97 tests across 20 modules
uv run ruff check .       # Lint

Project Structure

workflow-patterns/
├── src/workflow_patterns/
│   ├── models.py                  # Node, Edge, Workflow, Pattern + 80+ node type mappings
│   ├── parser/parse.py            # Robust n8n JSON parser (handles format inconsistencies)
│   ├── patterns/analyzer.py       # Pattern extraction, node stats, Jaccard similarity
│   ├── translator/claude_code.py  # Pattern -> Claude Code architecture mapping
│   └── mcp_server/server.py       # 4 MCP tools for Claude Code integration
├── examples/
│   ├── ai-chatbot/                # 22 tests — streaming API, 5 personas
│   ├── ai-content-creation/       # 30 tests — Claude API, 60 curated feeds
│   ├── email-automation/          # 25 tests — 5 templates, HTML + SMTP
│   ├── scheduled-notifications/   # 60 tests — rule engine, urgency levels
│   ├── data-pipeline/             # 53 tests — filter, aggregate, sort
│   └── api-integration/           # 36 tests — REST client, sample fallback
├── scripts/
│   └── generate_site.py           # Static site generator with interactive wizard
├── docs/
│   └── index.html                 # Generated GitHub Pages site
├── tests/                         # 20 unit tests across 4 modules
├── evals/                         # 10 evaluation test cases
├── data/sample_workflows/         # 15 sample n8n workflows for development
├── .github/workflows/ci.yml       # CI: lint + test on push/PR
└── mcp.json                       # MCP server config for Claude Code

Data Source

Workflow data from n8nworkflows.xyz, an independent archive of 7,000+ public n8n workflow templates. The sample dataset includes 15 workflows for development; the full dataset (7,698 workflows) can be placed in data/all_workflows/.

License

MIT