What is JSON?
JSON stands for JavaScript Object Notation. It is a lightweight text format for storing and exchanging data in a structured way. Readable by people and machines.
JSON originated as part of JavaScript, but today it is used everywhere: in web applications, APIs, configuration files, AI tools and even in spreadsheets. It is the universal language that systems use to share data with each other.
A JSON file is simply a text file with the extension .json. You can open it in any text editor, and the structure is so simple that you can read and write it after five minutes.
In short: JSON = structured data as text. It works everywhere, you need no special software, and both people and computers understand it.
The building blocks of JSON
JSON has only a few building blocks. Objects (with curly braces) contain key-value pairs. Arrays (with square brackets) contain lists of values. Values can be text, numbers, booleans (true/false), null, objects or arrays. That is all there is.
A simple example
Suppose you want to store a customer's details. In JSON that looks like this: an object with fields such as "name", "email", "company" and "orders". Each field has a clear name and a value. Orders can be a list of several items, each with their own fields.
This is the big advantage of JSON: it is hierarchical. You can nest, group and structure data in a way that makes sense for your application.
Why JSON instead of a database?
A database is powerful but complex. For many applications JSON is simpler, faster and more than sufficient.
No installation needed
A database requires server software, configuration, maintenance and often costs too. A JSON file is a simple text file that you can open anywhere. No MySQL, no PostgreSQL, no hosting needed.
Readable and editable
You can open a JSON file in Notepad, VS Code or any other text editor. Try that with a database file. JSON is directly readable, which makes it ideal for configurations, templates and small datasets.
Perfect for small to medium-sized datasets
Do you have a list of 10 customers, 50 products or 200 orders? JSON handles that effortlessly. Only with thousands of records and complex relationships does a database become truly necessary.
When do you choose a database after all?
| JSON is ideal for | A database is better for |
|---|---|
| Configuration files | Thousands of simultaneous users |
| Small lists and datasets | Complex relationships between tables |
| Data exchange between tools | Real-time transactions |
| Prototypes and experiments | Advanced queries |
| AI prompts and templates | Security and access control |
The rule of thumb: If you would keep your data in a spreadsheet, you can probably do it in JSON too. Only when you need Excel-like functions, formulas or several simultaneous users do you consider a database.
JSON in practice: structure and syntax
The rules of JSON are simple. Here you learn the syntax and the most common patterns.
The basic rules
An object contains key-value pairs between curly braces. Each key is in quotation marks, followed by a colon and the value. Pairs are separated by a comma.
An array is an ordered list of values between square brackets. Values are separated by commas. An array can contain text, numbers, objects or other arrays.
Text is always in double quotation marks. Numbers have no quotation marks. Booleans are true or false (without quotation marks). Null indicates an empty value.
Common mistakes
The most common mistake in JSON is a missing or extra comma. There must be no comma after the last item in an object or array. Other common mistakes: using single quotation marks (JSON requires double ones), or adding comments (JSON does not support comments).
Tip: Use a JSON validator such as jsonlint.com to check your files. Or ask Claude: "Check whether this JSON is valid." Claude finds errors immediately and explains what is wrong.
Storing data in JSON files
From configuration to customer details: practical patterns for storing data in JSON.
Configuration files
One of the most common uses of JSON is storing settings. Think of the colours of your brand identity, the texts on your website, or the parameters for an AI tool. You store them in a .json file and read them in when needed.
The advantage: if you want to change a colour, you change one value in the JSON file. You do not need to dive into the code. This separates configuration from functionality.
Lists and collections
JSON is perfect for keeping lists: products, customers, orders, tasks, events. Each list is an array of objects, where every object has the same structure. This makes it easy to add, edit or remove items.
Hierarchical data
What sets JSON apart from a simple CSV is the ability to nest data. A customer can have several contacts, each with their own phone numbers. An order can contain several lines, each with a product, quantity and price. This hierarchy is difficult in CSV, natural in JSON.
Practical: Keep your JSON files together with your project in a clear folder structure. Use names such as config.json, customers.json or orders.json. That way everyone knows immediately what is in them.
Example: storing your brand identity
Store the complete visual identity of your company in a JSON file: primary colour, secondary colours, font, logo path and standard texts. Hand this file to Claude with every project and your designs are always consistent.
Exchanging data between systems
JSON is the standard language for data communication. Almost every API, webhook and integration tool speaks JSON.
APIs and webhooks
When two systems exchange data, they almost always do so in JSON. Your web shop sends an order to your accounting software in JSON. Your website receives contact form submissions as JSON. A webhook from a payment provider sends payment confirmations in JSON.
This makes JSON essential for anyone who connects systems to each other, whether through tools such as n8n, Zapier or manually through code.
Importing and exporting
Many tools support JSON import and export. You can export data from a spreadsheet to JSON, process it with a script or AI, and import it again into another system. This is a powerful way to transform data without a database.
Send order data as JSON to your accounting package. Customer name, items, amounts and VAT in a structured format.
Forward contact form submissions as JSON to your CRM system. Name, email, message and date neatly structured.
Convert spreadsheet data to JSON and hand it to Claude for analysis, reporting or transformation.
Share project settings as a JSON file with team members. Everyone works with the same colours, texts and parameters.
Tip: Ask Claude to convert data. "Convert this Excel table to JSON" or "Turn these customer details into a JSON file" works flawlessly. Claude understands the structure and creates a correct file.
JSON and AI: smart combinations
JSON and AI tools are a perfect combination. AI understands JSON, generates it and processes it effortlessly.
Structured output from AI
One of the most powerful applications: ask Claude to give answers in JSON format. Instead of a wall of text you get structured data that you can use directly in your application, dashboard or workflow.
Example: "Analyse this customer list and give a summary per customer in JSON with the fields: name, sector, revenue_category and recommendation." You get an array of objects that you can import directly.
JSON as input for AI
Give Claude a JSON file as context and ask questions about it. "Which customer has the highest revenue?" or "Summarise all orders from this week." Claude reads the structure and gives targeted answers.
MCP and JSON
The Model Context Protocol (MCP) communicates entirely in JSON. Every tool call, every result and every configuration is a JSON object. If you build or use MCP servers, JSON knowledge is indispensable.
Powerful combination: Use JSON as the link between your data, your AI tools and your applications. Export data as JSON, let AI process it, and import the result back into your system. This is the core of modern AI workflows.
Practical example
You have a spreadsheet with product data. Export it as JSON, give it to Claude with the instruction "Write an appealing product description in Dutch for each product." Claude delivers a new JSON file with the same structure plus the descriptions. Import this into your web shop. Done.
JSON in AI workflows: examples
Concrete scenarios in which JSON forms the bridge between your data and AI applications.
Store reusable prompts as JSON with variables. Claude fills in the variables based on your input. Ideal for standard documents.
Retrieve data as JSON, have Claude analyse and summarise it, and generate a PDF report. The whole chain runs on JSON as the data format.
A JSON file with texts in Dutch. Claude translates each field into French, German and English. You get one JSON back per language.
Plan your social media posts in JSON: date, platform, text and image. Claude generates the texts, you schedule them.
JSON Schema: enforcing structure
If you work with large amounts of data or several team members, you want to enforce that JSON files follow a fixed structure. JSON Schema is a standard with which you define which fields are required, which data types are valid and which values are allowed.
Ask Claude to generate a JSON Schema based on an example. Claude analyses the structure and creates a schema that you can use to validate future files. This prevents errors and inconsistencies.
Pro tip: Always give Claude an example of the desired JSON structure with your instruction. This works as a schema and makes sure the output has exactly the format you need.
Tips, pitfalls and best practices
Avoid common mistakes and work more efficiently with JSON thanks to these practical guidelines.
Do's
Choose a style for your keys (camelCase or snake_case) and stick to it. Do not mix styles within the same file. This makes your data predictable.
Use a validator or ask Claude to check your file before you use it in production. A missing comma can crash an entire system.
Do not keep everything in one big file. Split data into logical files: customers.json, products.json, config.json. This makes maintenance simpler.
Don'ts
Passwords, API keys and personal data do not belong in plain JSON files. Use environment variables or a secure vault for sensitive data.
A JSON file is an ordinary file. If you accidentally overwrite or delete it, your data is gone. Use version control (Git) or make regular copies.
Advanced techniques
Once you have mastered the basics, you can use JSON for more complex scenarios and workflows.
JSON as an intermediate format
Use JSON as the link in a data pipeline. Retrieve raw data from a source (Excel, API, form), convert it to JSON, process it with AI or a script, and send the result on to its destination. JSON is lightweight enough to process quickly and structured enough to be reliable.
Combining several files
Instead of putting everything in a database, you can work with several JSON files that refer to each other through IDs. Customers.json contains customer details with a unique customer ID. Orders.json refers to that customer ID. This is a simple form of relational data without a database.
JSON and version control
Because JSON is plain text, it works perfectly with Git. Every change in your data is visible as a diff. You can go back to earlier versions, compare changes and collaborate with colleagues without conflicts. This is a big advantage over binary database files.
Automation with JSON
Build workflows that use JSON as the hub. A form submission generates a JSON object, that triggers a webhook, which sends the data to Claude for processing, and the result is stored as a new JSON record. All automatic, all traceable.
The next step: Once you are comfortable with JSON, explore the possibilities of MCP servers. With MCP you turn your JSON data into a live data source that AI assistants can consult directly. That is the bridge to the advanced Builder level.
Further reading and sources
Useful sources to keep learning and experimenting with JSON.
The official specification of the JSON format. Concise, clear and available in dozens of languages.
Online validator for JSON files. Paste your JSON in and see immediately whether it is valid and where any errors are.
Use Claude to generate, validate, transform and analyse JSON. Works seamlessly with JSON files in your projects.
The open standard that runs entirely on JSON. Essential if you want to connect AI tools to external data sources.
More guides, masterclasses and practical AI applications for the printing industry.
Not every solution
needs a database.Sometimes a file is enough,
a clear structure,
and the courage to think simple.
