
Structs
From raw text to structured JSON available as MCP Tools
What it does
Structs uses AI to extract structured data from any text, then turn it into dynamic visualizations — all from a single schema. Generate sample dataset from your json schema and create simple DataViz Structs allow you to store structured data available as MCP Tools to reuse in any context.
Does the same job
all alternatives →- DSData Structures and Algorithms in JavaScript2019 · github.com · ▲369
- JFJSON For You – Visualize JSON in graph or table views2024 · github.com · ▲211
After two years of improvement, I think it's time to share it with you all. Here’s a quick overview: - Common features include validation, formatting, minification, and more. - Visualize JSON in a graph or table view. - Structured comparison with fallback to text comparison. - Navigate though JSON using JSON pointer. - Supports jq. Would love to hear the community's questions, thoughts and comments!
Tabstack Structured ExtractionJun 2026 · tabstack.ai · ▲199Extract web data into structured JSON, no scraper required.
- DODocumind – Open-source AI tool to turn documents into structured data2024 · github.com · ▲169
Documind is an open-source tool that turns documents into structured data using AI. What it does: - Extracts specific data from PDFs based on your custom schema - Returns clean, structured JSON that's ready to use - Works with just a PDF link + your schema definition Just run npm install documind to get started.
- SOStructured output from LLMs without reprompting2023 · automorphic.ai · ▲174
Built a tool for transforming unstructured data into structured outputs using language models (with 100% adherence). If you're facing problems getting GPT to adhere to a schema (JSON, XML, etc.) or regex, need to bulk process some unstructured data, or generate synthetic data, check it out. We run our own tuned model (you can self-host if you want), so, we're able to have incredibly fine grained control over text generation. Repository: https://github.com/automorphic-ai/trex Playground: https://automorphic.ai/playground
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Hey HN, Henry from Cactus here! We previously released Cactus Needle, a 14MB agentic LLM for tool call, device use, and structured extraction for phones, wearables, smart homes, small robots and microcontrollers. We got really great feedback here, and have now incorporated the suggestions to release Needle 2. The whole model is a single 14MB binary that runs a full session in 28MB of RAM; 45m parameters at 2bit compression. Needle hits 500 tokens/sec decode speed on a Raspberry Pi 5, sits between 400-1,500 tokens/sec on VR devices like Meta Quest 3S and Apple Vision Pro, and ranges…
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