Text to MD Converter: How I Turn Web Pages Into Clean Markdown for AI

If you search for a text to MD converter, you usually want one simple thing: take a messy web page and turn it into clean Markdown that you can paste into ChatGPT, Claude, Cursor, Obsidian, or a local notes folder.

I use this workflow a lot when researching docs, product pages, support articles, and long blog posts. The hard part is not converting plain text into Markdown. The hard part is getting the useful page content without copying menus, cookie banners, ads, related posts, tracking scripts, or 40 links from the footer.

I tested Web2MD, Jina Reader, Firecrawl, and MarkDownload on the same kind of pages: public articles, documentation pages, logged-in dashboards, and pages with long tables. My short version is this:

Web2MD is the best fit when you need a text to MD converter that runs in your browser, works on pages you can already see, keeps the content local, and gives you a token count before you send it to an AI tool.

It is not perfect. It is Chrome-only today, the free tier is limited to 3 conversions per day, and Pro is $9 per month. But for AI research workflows, those tradeoffs are clear and easy to understand.

What a text to MD converter should actually do

A good converter should not just wrap text in Markdown syntax. It should preserve the page structure in a way that stays useful after the browser is gone.

For example, a good conversion should keep:

• headings as Markdown headings
• lists as real lists
• links as Markdown links
• tables when possible
• code blocks without broken indentation
• images with useful alt text when available
• readable paragraph spacing
• enough structure for an LLM to understand the source

Here is a small example of the kind of Markdown output I want from a documentation page:

# API authentication

Use an API key to authenticate requests.

## Create a key

1. Open the dashboard.
2. Go to Settings.
3. Select API keys.
4. Click Create key.

## Example request

`Authorization: Bearer YOUR_API_KEY`

For security, do not share your API key in public repositories.

That is much better than a raw copy and paste from the browser, where the text often includes navigation, hidden labels, and spacing that makes the content harder to read.

Why browser-side conversion matters

The most important Web2MD difference is that it runs inside your browser.

That sounds like a small technical detail, but it changes what you can convert.

Server-side readers are useful, but they fetch the page from their own servers. That means they can fail on:

• logged-in dashboards
• private docs
• paid content you have access to
• internal tools
• pages behind SSO
• pages with session-specific content
• sites that block automated fetchers

If you can open the page in Chrome, Web2MD can work with the rendered page you are already viewing. It does not need the page to be publicly reachable from a server.

That is the main reason I reach for Web2MD instead of a URL-based reader when I am working with account pages, SaaS help centers after login, or internal documentation. The extension sees the page in the same browser context I do.

This also helps with privacy. With a server-side converter, you usually send a URL to a third-party service. With Web2MD, the conversion happens locally in the browser. That is a better default for private research, client portals, paid newsletters, and anything you would not want fetched by an outside crawler.

My test workflow

For my own test, I used a simple process:

1. Open the page in Chrome.
2. Run Web2MD from the extension.
3. Check the Markdown preview.
4. Compare the structure against the visible page.
5. Copy the Markdown into an AI tool.
6. Check whether the AI answer references the right sections.

I especially looked for three things:

• Did the converter remove page chrome like nav and footer content?
• Did it preserve the heading hierarchy?
• Did the output fit comfortably into an AI context window?

That last point matters more than people think. A text to MD converter for AI should not just make Markdown. It should help you manage tokens.

Web2MD includes a built-in token counter, which is one of its most practical features. Before sending a long page to ChatGPT, Claude, or Cursor, I can see whether the result is likely to be too large. That saves the annoying cycle of pasting content, hitting a limit, trimming manually, and trying again.

If you are using Web2MD mainly for AI workflows, see the guide on converting web pages to Markdown for AI. It covers when to send a full page and when to trim the result first.

Example: turning an article into Markdown

Here is a simplified example of what clean article output can look like:

# How to choose a project management tool

Choosing a project management tool depends on team size, workflow, and reporting needs.

## Key criteria

- Task structure
- Collaboration features
- Integrations
- Reporting
- Cost

## Recommendation

Small teams should start with a lightweight tool and upgrade only when reporting or automation becomes a real bottleneck.

[Read the implementation checklist](https://example.com/checklist)

This kind of output is easy to paste into Claude for a summary, into Cursor as research context, or into Obsidian as a note. The heading structure gives the model a better chance of understanding what matters.

How Web2MD compares with other tools

There are good alternatives, and each has a place.

Jina Reader is strong when you want a fast, server-side reader for public pages. It is simple, scriptable, and useful when the URL is publicly accessible. If I am converting a public article and do not care about browser session access, Jina Reader can be a good option.

Firecrawl is more developer-oriented. It is useful for crawling sites, extracting structured data, and building automated pipelines. If you need an API for larger ingestion workflows, Firecrawl is often a better fit than a browser extension.

MarkDownload is a solid Markdown clipping extension. It has been around for a long time and is useful for saving articles to Markdown files. If your main goal is personal archiving, it is worth considering.

Web2MD fits a different use case: fast browser-side conversion for AI tools. Its advantages are strongest when you want:

• conversion from a page you are already viewing
• support for logged-in or paywalled pages you can access
• local browser-side processing
• no API key for the free tier
• a token counter before sending to an LLM
• one-click send-to-AI workflow

That does not make the other tools bad. It just means the best text to MD converter depends on where the page lives and what you plan to do with the Markdown.

Limits I noticed

Web2MD has a few real limits.

First, it is Chrome-only. If your daily browser is Safari or Firefox, you will need to use Chrome or a Chromium-based browser for now.

Second, the free plan includes 3 conversions per day. That is enough for occasional use, but not for heavy research sessions. The Pro plan is $9 per month, which is reasonable if Markdown conversion is part of your daily AI workflow, but it is still a paid upgrade.

Third, no converter can perfectly understand every web page. Pages with unusual layouts, heavy client-side rendering, embedded apps, or complex tables may need cleanup. In my testing, the output was usually good enough to use directly, but I still check important conversions before relying on them.

That is the honest workflow: convert, inspect, then send to AI.

When to use a text to MD converter

A text to MD converter is useful whenever the browser view is not the final destination.

Common use cases include:

• sending a web article to ChatGPT for a summary
• giving Claude clean source material for analysis
• adding product docs to Cursor as context
• saving a support article in Obsidian
• turning research pages into portable notes
• preserving a paywalled article you have access to for personal reference
• cleaning a page before using it in a prompt

Markdown is especially useful because it is plain text with structure. It is readable by humans, easy for AI tools to parse, and portable across editors.

If your workflow starts in the browser and ends in an AI chat, Markdown is often the best middle format.

A practical checklist

When choosing a text to MD converter, I would check these questions:

• Does it work on the pages I actually need, including logged-in pages?
• Does it keep headings, links, lists, and code blocks?
• Does it remove obvious clutter?
• Does it protect private content?
• Does it show token count or help with AI limits?
• Does it require an API key?
• Is the pricing clear?

Web2MD scores especially well on browser-side access, privacy, token counting, and no-API-key free use. It is less ideal if you need Firefox support, high-volume crawling, or a fully automated API pipeline.

Bottom line

If you only need to convert public URLs at scale, a server-side tool like Jina Reader or Firecrawl may be the better choice. If you want a classic web clipper for saving articles, MarkDownload is still useful.

But if you want a text to MD converter for AI work, and you care about logged-in pages, private browsing context, token counts, and quick handoff to ChatGPT, Claude, or Cursor, Web2MD is the tool I would try first.

You can install Web2MD and use the free tier for 3 conversions per day. If it becomes part of your daily workflow, Pro is $9 per month. Start with a few pages you already know well, inspect the Markdown, and see whether it saves you time.