web2md-mcp
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@web2md-mcp fetch https://example.com/blog/post"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
web2md-mcp
MCP server that fetches any web URL and converts it to clean Markdown via the web2md service (Crawl4AI backend). Designed to be hosted on the ModelScope MCP Hub so any pure-network MCP client can call it without running anything locally.
What it does
Exposes one tool fetch(url, quality, anti_bot) → returns
{success, markdown, html, metadata}. It does not bundle Crawl4AI; it
calls the already-deployed web2md REST API (/v1/fetch), so the hosted image
stays tiny and deploys fast.
Related MCP server: agent-web
ModelScope MCP Hub — 可托管部署 (recommended)
Per the official MCP creation doc, hosted deployment of a Python server requires
a PyPI package invoked via uvx (GitHub/Docker sources are NOT supported
for hosted deployment). This package is published to PyPI as web2md-mcp.
Create the MCP service (自定义创建 → 可托管部署) and paste this STDIO config.
The Hub auto-extracts the env block into its env-var form:
{
"mcpServers": {
"web2md": {
"command": "uvx",
"args": ["web2md-mcp"],
"env": {
"WEB2MD_BASE": "https://seaair-web2md.ms.show",
"WEB2MD_API_KEY": "<WEB2MD_API_KEY>"
}
}
}
}The Hub runs uvx web2md-mcp inside its FC runtime (STDIO transport), connects,
and exposes a public endpoint https://mcp.api-inference.modelscope.net/<id>/mcp.
Fill the real key in <WEB2MD_API_KEY> when creating.
Note: the config JSON must contain no comments — the Hub's validator rejects commented JSON.
Self-host (local / Docker, optional)
pip install web2md-mcp
WEB2MD_API_KEY=web2md-bcce3f564124cb40ff41244b6597a209 web2md-mcp
# then point your client at the resulting MCP server (stdio)Or build the Docker image (for your own registry / FC custom image):
FROM python:3.11-slim
WORKDIR /app
COPY requirements.txt .
RUN pip install -r requirements.txt
COPY web2md_mcp.py .
CMD ["python", "web2md_mcp.py"]Env vars
Key | Default | Description |
|
| web2md REST base URL |
| (empty) | your web2md API key |
Tool
fetch(url, quality="fast", anti_bot="auto") → {success, markdown, html, metadata}
Available Tools
1 toolfetchA
Fetch a web page URL and return its main content as clean Markdown.
Uses the web2md service (Crawl4AI) behind the scenes. Best for feeding article / documentation text into an LLM or RAG pipeline.
Inputs: url (required), quality, anti_bot. Returns: object
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
Loading tool schema changelog…
TDQS
Scored across 1 tool
Only one tool exists, so there is no possibility of confusion or overlap. The tool's purpose is clearly defined and distinct.
With a single tool named 'fetch', there is no inconsistency or mixed conventions. The name is a clear verb that matches its action.
A single tool is on the thin side, but it is appropriate for a focused web-to-Markdown service. The minimal surface aligns with the server's narrow scope, though more tools could be added for broader utility.
The fetch tool fully covers the stated purpose of converting a web page to clean Markdown. There are no obvious gaps for the core use case, as the operation is self-contained.
Maintenance
Related MCP Connectors
Fetch any URL and get clean Markdown. Web scraping for AI agents.
Converts any URL to clean, LLM-ready Markdown using real Chrome browsers
Web scraping for AI agents. Converts URLs to clean, LLM-ready Markdown with anti-bot bypass.
Read any web page as clean Markdown for AI agents: fetch, search, metadata, links. SSRF-safe.
Related MCP Servers
- AlicenseAqualityDmaintenanceConverts URLs and raw HTML to clean Markdown, enabling AI assistants to read web pages for summarization, analysis, or ingestion.213 npm1MIT
- AlicenseNot gradedqualityDmaintenanceConverts URLs into clean, LLM-ready markdown, respecting robots.txt and never bypassing anti-bot measures or paywalls.MIT
- AlicenseNot gradedqualityAmaintenanceEnables AI agents and MCP clients to fetch web pages or crawl sites and convert them into clean, token-efficient Markdown while preserving links.MIT
- AlicenseNot gradedqualityAmaintenanceEnables MCP clients and AI agents to fetch webpages and crawl sites, strip noise, and convert content into clean, link-preserving Markdown with caching and configurable multi-page depth while minimizing token usage.MIT