Universal Format Converter: One API for JSON, CSV, Markdown & PDF

Every integration project eventually hits the same wall: data arrives as CSV but your pipeline expects JSON. A partner sends XML. Marketing exports Excel. Docs live in Markdown but the CMS wants HTML. You could write a converter for each pair — and maintain them forever — or call one API that already handles the matrix.

The Universal Data Format Converter API is built for that second path. One POST /convert endpoint, 15+ formats, structured data and documents. v2.1 adds Markdown → HTML/PDF and HTML → Markdown (strict, readable, or LLM-friendly modes).

Structured data: the obvious use cases

• JSON ↔ CSV — Export API responses for analysts; ingest spreadsheet uploads back into your app.
• XML ↔ JSON — Bridge legacy SOAP/XML feeds into modern JSON services without bespoke parsers.
• Excel → JSON — Turn uploaded spreadsheets into arrays your backend can validate and store.
• YAML ↔ JSON — Config files, CI fixtures, and API payloads in the format each tool expects.

All conversions are stateless: nothing is stored. Payloads up to 20MB; PDF table output has documented row/column limits.

Documents: Markdown and HTML

Structured conversion is table stakes. What breaks teams is document conversion — rendering Markdown with proper code highlighting, turning HTML pages into clean Markdown for RAG pipelines, or producing shareable PDFs from README files.

The converter handles:

• Markdown → HTML — Self-contained HTML with GitHub-style CSS, GFM tables, task lists, footnotes.
• Markdown → PDF — Document PDF via pdfmake (no headless browser).
• HTML → Markdown — Three modes: strict, readable, or llm-friendly for AI ingestion pipelines.

For HTML-only Markdown extraction, see also the dedicated HTML to Markdown Converter API — same modes, focused endpoint.

When to use a converter vs. normalization

Format conversion answers: “What syntax is this data in?” Normalization answers: “What does this data mean across vendors?” They stack well:

• Convert CSV export → JSON with the format converter.
• Normalize JSON from five retailers with the Retail Data Normalization API.
• Validate the canonical shape with the JSON Schema Validator.

See Building Data Combiners for the full pipeline pattern.

Try it without writing code

The catalog page includes a live playground: pick source and target formats, paste sample data or upload a file, and run against RapidAPI. Code snippets for cURL, JavaScript, Python, and Java update automatically.

Related reading: Three APIs That Keep Your JSON On Track · API Payload Validation Best Practices