James Allman | JA Technology Solutions LLC
Markdown Table Converter
Convert GitHub Flavored Markdown tables to CSV, Excel, JSON, and 8 other formats.
Markdown Table Converter
Paste a Markdown table (GitHub Flavored Markdown, pipe-delimited with the `|---|---|` separator row) or upload a `.md` file and convert it to CSV, TSV, pipe-delimited text, JSON, JSONL, Excel, YAML, XML, HTML, or SQL INSERT statements. Auto-detects the table within longer documents — preamble prose, headings, and trailing paragraphs are ignored. Tolerates ragged rows, escaped pipes (`\|`), optional leading and trailing pipes, and the `:---` / `---:` / `:---:` alignment markers. Force Text mode preserves leading zeros in IDs, ZIP codes, and account numbers when output as JSON or Excel. Heavy parsing and output generation run in a Web Worker so the UI stays responsive on large tables; you can cancel an in-progress conversion at any time. Runs entirely in your browser; pasted tables and uploaded files never leave your machine.
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The Markdown Table Format
Markdown tables are part of GitHub Flavored Markdown (GFM) and the GitHub-extended CommonMark spec. The shape is a header row, a separator row of dashes (with optional colons for column alignment — :--- left, ---: right, :---: center), and any number of data rows. Cells are separated by pipes; leading and trailing pipes are optional. Within a cell, a literal pipe is written as \|. Cell width padding is purely cosmetic and gets stripped on parse. The format is everywhere: README tables, pull request descriptions, issue comments, Jira and Confluence, Slack, Discord, internal wikis, AI assistant output, and almost anything that goes through a markdown processor.
Why Round-Tripping Through CSV Is Useful
The most common reason to convert a Markdown table into something else is that you want to do something with the data: pull a table out of a README so you can pivot it in Excel, dump a competitor comparison from a doc into a JSON config file, extract a list of SKUs from a PR description into a database load, or move structured data between a markdown-based documentation system and a spreadsheet-based reporting workflow. Manual copy-paste loses alignment, drops separator-row alignment markers as junk rows, and chokes on escaped pipes. This tool handles all of those cases automatically, then lets you drive the output format from a single dropdown.
When You Need an Automated Pipeline
This tool handles one-off conversions. For documentation pipelines that extract tables from markdown sources on every commit, sync product comparison tables between a marketing CMS and a spreadsheet, generate database seed files from documentation, or pull SKU lists out of release notes for downstream systems, the work belongs in a build step or scheduled job rather than a browser. I build documentation and content pipelines that ingest markdown, extract structured data, validate it against schemas, and deliver clean output to downstream systems. Need help? ETL and data pipelines · Custom application development. Have a question? Ask James.
All tools run entirely in your browser. Your data never leaves your machine.