n8n-nodes-parser-bigboss
v1.0.6
Published
Smart parser node for AI outputs - extracts and structures JSON/YAML/XML/Lists dynamically.
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🧩 n8n-nodes-parser-bigboss
Parser BigBoss is the ultimate utility for turning messy AI output into structured data. It automatically detects and cleans JSON, YAML, and XML from any text block, ensuring your workflows never break due to a trailing comma or extra markdown from an LLM.
🚀 Key Features
- Smart Auto-Detect: Automatically finds and extracts structured data hidden inside large text blocks or markdown code blocks.
- Loose JSON Parsing: Uses JSON5 to handle common AI mistakes like trailing commas, single quotes, or missing property quotes.
- Multi-Format Support: One node to rule them all: JSON, YAML, and XML.
- Flexible Error Handling: Choose to return
null, the original text, or trigger a node error when parsing fails. - Output Control: Spread properties directly to the node output or wrap them in a specific property name.
🕹️ Parsing Strategies
1. Auto-Detect (Smart)
The BigBoss choice. It scans the text, identifies the likely format, handles markdown stripping, and returns parsed data instantly.
2. Extract JSON
Forces JSON extraction. Optimized for cleaning LLM responses that include chatty text before or after the JSON block.
3. Extract YAML / XML
Reliable extraction for configuration files or legacy system outputs.
🛠️ Usage
- Input Text: Pass the raw text from an OpenAI, Anthropic, or any LLM node.
- Select Strategy: Usually,
Auto-Detect (Smart)is all you need. - Handle Errors: Set your preference for failed parses (e.g., return original text for manual review).
- Result: Your workflow continues with perfectly structured JSON objects.
📥 Installation
npm install n8n-nodes-parser-bigboss🏗️ Build from Source
npm install
npm run build👑 The BigBoss Standard
Part of the BigBoss ecosystem—n8n nodes built for reliability, scale, and professional workflows. Say goodbye to "JSON Parse Error" forever.
📬 Contact
Have questions or need support? Reach out at [email protected].
License
MIT
