org.web2md/web2md
MCP Server for Web2MD — convert URLs to Markdown from Claude Desktop, Cursor, etc.
Que pouvez-vous faire avec org.web2md/web2md ?
- Finds the actual article. Strips navigation, sidebars, ads, cookie banners,
- Preserves structure. Headings, lists, tables, and fenced code blocks survive
- Reports tokens. Estimated counts for both the original HTML and the cleaned
- Runs anywhere. Uses linkedom
Installation
Ajoutez ceci à la configuration MCP de votre client (Claude Desktop : claude_desktop_config.json ; Cursor : .cursor/mcp.json ; VS Code et les autres utilisent la même forme « mcpServers »).
web2md-mcp-serverclaude mcp add web2md -e 'WEB2MD_API_KEY=<your web2md_api_key>' -- npx -y web2md-mcp-server@0.12.2
{
"mcpServers": {
"web2md": {
"command": "npx",
"args": [
"-y",
"web2md-mcp-server@0.12.2"
],
"env": {
"WEB2MD_API_KEY": "<your web2md_api_key>"
}
}
}
}
Variables d'environnement
WEB2MD_API_KEYsecret Web2MD API key (w2m_...). Get one at https://web2md.org/dashboard, or run npx web2md-cli login instead.
Documentation
Tirée du README du projet sur GitHub, actualisée chaque semaine. Les liens ouvrent GitHub.
web2md-core
Turn messy HTML into clean, LLM-ready Markdown.
This is the extraction and conversion engine behind Web2MD. It is a pure library — give it an HTML string, get Markdown back. No network calls, no API key, no account. Nothing in this package talks to a server.
npm install web2md-core
Why convert at all
Feeding raw HTML to a language model wastes most of your context window on markup, navigation, and ads. Converting first cuts that down and gives the model a document it can actually follow.
The library reports both numbers so you can see the difference:
import { convertToMarkdown } from 'web2md-core'
const result = convertToMarkdown(html, { url: 'https://example.com/post' })
console.log(result.markdown)
console.log(result.metadata.originalTokenCount, '→', result.metadata.tokenCount)
// e.g. 417 → 281
convertToMarkdown returns null when it cannot find a main content block —
check for that rather than assuming a result.
What it does
- Finds the actual article. Strips navigation, sidebars, ads, cookie banners, and footers, keeping the content a reader came for.
- Preserves structure. Headings, lists, tables, and fenced code blocks survive the round trip — that structure is what lets a model answer questions about one specific section.
- Reports tokens. Estimated counts for both the original HTML and the cleaned Markdown, plus helpers to split or trim for a target context window.
- Runs anywhere. Uses linkedom for parsing, so it works in Node without a browser.
API
convertToMarkdown(html, options?)
The main entry point. Note the signature takes two arguments — the URL goes
inside options, not as a positional parameter:
convertToMarkdown(html, { url: 'https://example.com/post' })
| Option | Default | Meaning |
|---|---|---|
url | — | Source URL. Used to resolve relative links and fill metadata.url. |
includeLinks | false | Keep <a> as Markdown links. Off by default because link URLs are often the bulk of the tokens on navigation-heavy pages. |
includeImages | false | Keep images. Off by default for the same reason. |
includeMeta | false | Prepend a metadata block (title, source, timestamp). |
customRule | — | A CustomRule for site-specific extraction. |
detectCodeLanguage | false | Try to infer the language of fenced code blocks. |
includeLinks and includeImages default to off. That is deliberate — the
primary use case is feeding an LLM, where both are usually noise. Turn them on
when you are archiving rather than summarising.
Other exports
quickConvert(html, url?) // same result, but with links, images and
// metadata turned ON — the "archive it" preset
extractContent(html, url?) // main content element, before conversion
htmlToMarkdown(html, options?) // low-level conversion, no extraction
countTokens(text) // token estimate
splitByTokens(md, limit) // chunk for RAG ingestion
optimizeForContextWindow(md, model)
htmlLooksLikeLoginWall(html) // detect login walls so you can fail loudly
MODEL_CONTEXT_LIMITS // context sizes for common models
Markdown → sanitized HTML (via DOMPurify), for previewing output:
renderMarkdownSync(md)
renderMarkdownFull(md) // async; includes syntax highlighting
renderMarkdownWithFormulas(md) // KaTeX math
getPageHTML() and getSelectionHTML() read document directly and therefore
only work in a browser. They throw in Node — that boundary is intentional.
Site-specific extraction
Generic extraction handles most pages. When a site needs special treatment, pass a rule:
convertToMarkdown(html, {
url: 'https://example.com/thread',
customRule: {
name: 'Example forum',
domain: 'example.com',
contentSelector: '.thread-body',
removeSelectors: ['.signature', '.ad-slot'],
},
})
Scope
This package covers extraction and conversion. It does not include Web2MD's browser extension, hosted API, or account system — those stay in the product.
Contributions to extraction quality are especially welcome: if a site converts badly, an issue with the URL and what went wrong is genuinely useful.
License
MIT
Questions fréquentes
Qu'est-ce que org.web2md/web2md ?
MCP Server for Web2MD — convert URLs to Markdown from Claude Desktop, Cursor, etc.
Comment installer org.web2md/web2md ?
Il s'exécute sur votre machine. Dans Claude Code : claude mcp add web2md -e 'WEB2MD_API_KEY=<your web2md_api_key>' -- npx -y web2md-mcp-server@0.12.2. Pour les autres clients, collez la configuration JSON de cette page dans leurs réglages MCP.
Faut-il une clé API pour org.web2md/web2md ?
Oui. Il attend WEB2MD_API_KEY, à renseigner dans sa configuration.
org.web2md/web2md est-il open source ?
Oui. Son code est sur GitHub sous licence MIT.
Qui maintient org.web2md/web2md ?
Il est publié par io-oi-ai. AI.tn le référence sans le maintenir ni le recommander.
Issu du registre MCP officiel. Être listé n'est pas une recommandation : vérifiez le code et les permissions d'un serveur avant de lui donner accès à vos données.