JSON to Markdown converter

JSON to Markdown writes a GFM table from the flattened record set, making it useful for docs but lossy for nested JSON structure.

Converted with Table engine · nothing stored
Free: 5 conversions a day · 5 MB each
Higher limits →

From real runs

What you get — and what changes

Element	Result	What happens
Top-level records	Kept	The two JSON records became two Markdown data rows below a shared header.
Nested properties	Changed	customer.name, customer.city, and extra.gift appeared as dotted Markdown column headers.
Arrays	Changed	The tags arrays were printed as JSON strings inside table cells, including quotes and brackets.
Nulls	Changed	Null fields became empty Markdown cells, which read as blank rather than as the word null.
Unicode values	Kept	München, Zoë, and 東京 were visible in the generated Markdown without escaping.
Pipe safety	Changed	Any vertical bars in values would be escaped by the Markdown writer to keep table columns aligned.

Top-level records Kept
The two JSON records became two Markdown data rows below a shared header.
Nested properties Changed
customer.name, customer.city, and extra.gift appeared as dotted Markdown column headers.
Arrays Changed
The tags arrays were printed as JSON strings inside table cells, including quotes and brackets.
Nulls Changed
Null fields became empty Markdown cells, which read as blank rather than as the word null.
Unicode values Kept
München, Zoë, and 東京 were visible in the generated Markdown without escaping.
Pipe safety Changed
Any vertical bars in values would be escaped by the Markdown writer to keep table columns aligned.

Sample conversions

Flattened docs table

Input: JSON: [{"id":"001","customer":{"name":"Ada","city":"München"},"tags":["priority","quoted, comma"]}]
Output: Markdown header included | id | customer.name | customer.city | tags | zip | active | total | due | empty | extra.gift |.

Blank null cells

Input: Both JSON records had empty: null, and the first record lacked extra.gift.
Output: Markdown rows left those cells empty; the second row ended with true under extra.gift.

A real JSON → Markdown run

We converted our JSON sample (557 B) with Table engine on 2026-09-11. It took 1 ms and produced a 318 B Markdown file, 43% smaller than the input. The engine raised no warnings.

Input · sample.json · 557 B

Array of 4 objects; keys: company, stage, arr, owner, close_date

Records: 4
Keys: company, stage, arr, owner, close_date

Output · sample.md · 318 B

0 headings, 1 table, 0 list items, 0 code blocks, 0 image references

Headings: 0
Tables: 1
List items: 0
Code blocks: 0
Images: 0
Lines: 6

First lines of the output

| company | stage | arr | owner | close_date |
| --- | --- | --- | --- | --- |
| Northwind Traders | Proposal | 48000 | R. Ayers | 2026-10-14 |
| Contoso Ltd | Negotiation | 120000 | P. Ng | 2026-09-30 |
| Fabrikam | Qualified | 22500 | R. Ayers | 2026-11-02 |
| Tailspin Toys | Won | 64000 | M. Okafor | 2026-09-03 |

Options and when to change them

flattenSeparator: Change it when dotted Markdown headers clash with existing property names.
arrayMode: Use explode when small arrays should become indexed Markdown columns instead of JSON text.
encoding: Use latin1 only for non-UTF-8 JSON-like files that still parse after decoding.

Do it yourself

pandas

bash

python - <<'PY'
import pandas as pd
df = pd.json_normalize(pd.read_json("input.json").to_dict(orient="records"))
df.to_markdown("output.md", index=False)
PY

Install tabulate for pandas Markdown output, and decide how arrays should be represented before publishing.

JSON to Markdown by API or MCP

The HTTP API and the MCP server run the exact engine this page uses (Table engine); the response carries the same warnings the web converter shows. Check support first with GET /api/v1/pairs?from=json&to=md.

curl

curl -X POST https://filetypeconverters.com/api/v1/convert \
  -H "Authorization: Bearer $FTC_API_KEY" \
  -F "file=@input.json" -F "from=json" -F "to=md" \
  -F 'options={"encoding":"utf-8"}' \
  --output output.md

Options this engine accepts for JSON → Markdown

Key	Applies to	Type	Default
encoding	Reading JSON	utf-8 · latin1	utf-8
flattenSeparator	Reading JSON	string	.
arrayMode	Reading JSON	json · explode	json

API reference

When this is the wrong conversion

Do not convert to Markdown when downstream code needs to parse the original JSON hierarchy.
If the data is large enough for analysis, CSV, Parquet, or SQL is usually easier to process than a Markdown table.

JSON to Markdown questions

Does JSON to Markdown create one table or many?

For the JSON array we tested, it created one GFM table. Every distinct flattened key became one column in that table.

How are JSON null values shown in Markdown?

They are blank cells in the table output. Readers will not see a literal null unless you replace those values before conversion.

Can Markdown preserve JSON arrays?

Only as text in this conversion. The default output showed arrays like ["priority","quoted, comma"] inside one cell.