A developer building an AI agent or RAG pipeline that reads the full content of a web page needs clean, structured Markdown, not a search result snippet. Tavily is a search and retrieval tool. Its Search endpoint returns ranked snippets, and its Extract endpoint returns page content as Markdown or text, but its documentation does not describe guarantees for heading hierarchy, table preservation, or code block integrity. For a developer who needs a documentation page, a blog post, or a product page with its structure intact, that can mean checking the output and post-processing it before a chunker can rely on it. EnConvert is a single REST endpoint that renders a web page and returns heading-aware Markdown with navigation chrome, banners, and sidebar content stripped, so structured Markdown is ready for an agent context window or chunking pipeline in one call.
Best Tavily Alternative for Markdown Output
EnConvert is a Tavily alternative that renders a web page and returns heading-aware Markdown with navigation and sidebar content stripped in one API call
Get API keyExample
import os
import requests
ENCONVERT_API_KEY = os.environ["ENCONVERT_API_KEY"]
PAGE_URL = os.environ["PAGE_URL"] # the web page URL to extract
# Step 1: Render the page and ask for Markdown with navigation chrome stripped
response = requests.post(
"https://api.enconvert.com/v2/perceive",
headers={
"X-API-Key": ENCONVERT_API_KEY,
"Content-Type": "application/json",
},
json={
"url": PAGE_URL,
"outputs": ["markdown"],
"only_main_content": True,
},
timeout=60,
)
response.raise_for_status()
perceived = response.json()
# A blocked or login-walled page returns 200 with no outputs; deductions say why
if perceived.get("error") or "markdown" not in perceived.get("outputs", {}):
raise RuntimeError(
f"Perceive failed for {PAGE_URL}: "
f"{perceived.get('error') or perceived.get('deductions')}"
)
# Step 2: The markdown is a signed artifact URL (valid 15 minutes). Plain GET, no API key.
markdown_response = requests.get(perceived["outputs"]["markdown"]["url"], timeout=60)
markdown_response.raise_for_status()
markdown = markdown_response.text
# Headings stay on one line and code fences keep their language, ready to chunk
print(markdown)
What you get back
Capability | EnConvert | Tavily |
|---|---|---|
Output format | Clean Markdown from Perceive, with navigation chrome and sidebar content stripped | Markdown or text, selectable per request via |
Heading structure preserved | Confirmed: headings, tables, and code blocks preserved with navigation chrome stripped | Not documented as a specific guarantee |
Full page content | Confirmed: full page rendered with navigation, banners, and sidebar content stripped | Confirmed: Extract returns full page content; advanced mode handles tables and embedded content |
File ingestion (PDF, DOCX, XLSX) | Ingest: PDF, DOCX, XLSX, CSV, Markdown, and plain text; chunks split at H1 to H3 boundaries, 512 word soft cap, tables and code blocks kept whole | Not documented as a file upload ingestion pipeline |
Document conversion | Convert: 45+ conversion routes across documents, images, and data formats | Not documented |
Summarisation endpoint | Distill: any URL or file to a clean summary in one call | Not documented as a dedicated URL or file summarisation endpoint |
MCP server | Native, exposes full ingestion toolkit as MCP tools | Confirmed: official hosted MCP server with search, extract, crawl, map, and research tools |
Free tier | 500 ops per month, no card required | 1,000 credits per month, no card required |
WHY ENCONVERT FOR MARKDOWN OUTPUT
Clean structured Markdown means heading hierarchy is preserved so chunking respects document structure, and navigation chrome and sidebar content are stripped before the response comes back. The same API covers file ingestion and summarisation, so your integration does not change when the agent’s input surface grows beyond web pages. Every EnConvert endpoint returns the same Markdown schema, so the code that handles a web page also handles a PDF or DOCX without branching.