MCP server with multi-tier fallback chain for fetching web content as clean markdown
MCP server with multi-tier fallback chain for fetching web content as clean markdown
Give your AI the ability to read the web. One command, no API keys required.
fetch — Long pages are truncated at maxLength with a notice telling the agent which startIndex continues the content. Structured output reports source, quality, contentLength, truncated, nextStartIndex, and cacheAgeSeconds so agfetch_batch — Fetch up to 10 URLs in parallel, each through the same handler/fallback chain.research — Search the web and fetch the top results in one call — replaces a search followed by several fetches.search — Uses Brave Search API if BRAVE_API_KEY is set, then SearXNG if SEARXNG_URL is set, then DuckDuckGo as an unreliable last resort. freshness and page are ignored by the DuckDuckGo fallback.extract — Extract specific values from a page as JSON instead of markdown prose — for when you need particular data, not the whole page. Honors per-domain auth and proxies.Compare MCP servers by category, or browse hosted MCP servers if you prefer an endpoint over a local process.
Check the linked publisher documentation and your connected client's tool list. Names and availability can vary with the server version and account permissions.
| Tool | What it does |
|---|---|
| fetch_batch |
{
"mcpServers": {
"intercept": {
"command": "npx",
"args": [
"-y",
"intercept-mcp"
]
}
}
}From the project documentation. Replace placeholders and example paths before connecting.
Retrieve public web pages as readable Markdown with the reference Fetch MCP server, including pagination for longer responses.
Use Firecrawl MCP to retrieve website content and extract information for research through Firecrawl’s API-backed web tools.
The original Chromium automation reference server — simple, screenshot-driven browser control.
Puppeteer-powered browser control that drives pages from the accessibility tree instead of pixels.
Automates browsers and APIs, enabling Large Language Models (LLMs) to interact with web pages for tasks like screenshot capture and JavaScript
Search built for AI, not humans — semantic web search that returns model-ready content, plus code context.