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- mcp
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size_categories:
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- 10K<n<100K
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- mcp
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size_categories:
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- 10K<n<100K
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---
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# n8n Automation Atlas: 36,405 n8n Workflows
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A curated collection of **36,405 unique n8n automation workflows**, organized and cleaned for AI training, research, and community use. This dataset combines high-quality synthetic workflows generated via a custom archetype engine with a massive pool of cleaned community templates.
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## 🚀 Project Links
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- **Main Repository:** [GitHub - Ker102/n8n-workflows-36k](https://github.com/Ker102/n8n-workflows-36k)
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- **Author:** [Ker102 on GitHub](https://github.com/Ker102)
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- **Explorer UI:** A Vue-based web application is included in the main repository to browse these workflows locally.
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## 📊 Dataset Statistics
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- **Total Unique Workflows:** 36,405
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- **Source Breakdown:**
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- **Repository & Synthetic:** ~12,500 unique functional scripts.
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- **Community (Cleaned):** ~23,900 unique community-contributed templates.
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- **Format:** JSON / JSON Lines (.jsonl)
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- **License:** Apache 2.0
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## 🧠 Methodology: The Combinatorial Archetype Engine
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The majority of the synthetic workflows in this dataset were generated using a **Combinatorial Archetype Engine**. This engine ensures high validity and diversity by using mathematically proven combinations of compatible nodes.
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### How it works:
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- **Equivalency Groups:** Nodes are grouped by function (e.g., Databases, Messaging, AI, DevOps).
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- **Archetypes:** Verified "skeletons" of common automation patterns (e.g., "Form to Database & Notify", "AI Summarizer", "RAG Ingestion").
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- **Combinatorial Expansion:** The engine iterates through every valid combination of nodes for each archetype, multiplying the output volume while maintaining structural integrity.
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## 🛠️ Data Quality & Cleaning
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The community portion of this dataset (sourced from the `n8n_workflows_templates_dataset`) underwent an intensive cleaning process:
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- **JSON Normalization:** Stringified JSON values were parsed into valid nested objects.
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- **Structural Verification:** Every workflow was checked for the presence of `nodes` and `connections`.
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- **Deduplication:** Workflows were deduplicated based on unique structural fingerprints and IDs.
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- **Metadata Extraction:** Node counts and integration types were extracted to allow for easy filtering.
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## 📂 Directory Structure (in GitHub)
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- `workflows/`: Contains the raw JSON files for each workflow.
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- `web/`: A Vue + Vite application serving as a "Workflow Explorer" UI.
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- `scripts/`: Tools for manifest generation, synthetic creation, and data cleaning.
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## 🤝 Community & Support
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This project is maintained by **Ker102**. If you find this dataset useful, please consider:
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- Giving the [GitHub repository](https://github.com/Ker102/n8n-workflows-36k) a ⭐.
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- Following [Ker102 on GitHub](https://github.com/Ker102) for more automation and AI-related projects.
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- Contributing new archetypes or reporting issues in the GitHub repository.
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---
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*Note: These workflows are provided as-is for research and development purposes. Always review workflows before importing them into a production n8n environment.*
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