NetLens

An MCP server for unobstructed web reading. It fetches any URL directly with browser-like headers — past robots.txt and naive bot blocks — and returns the full page as clean, ad-stripped Markdown, not a summary. Plus web search that returns real links. Zero dependencies: pure Python standard library.

Built for AI Agents

AI agents constantly hit pages their built-in tools can't read. NetLens fixes the three usual reasons a fetch comes back empty or useless:

It does not try to defeat JavaScript/Cloudflare challenge pages or CAPTCHAs — that's out of scope by design. When a page is a hard block, the HTTP status is surfaced honestly rather than faked.

Installation

npm (via npx):

{
  "mcpServers": {
    "netlens": {
      "command": "npx",
      "args": ["-y", "netlens-mcp"]
    }
  }
}

PyPI (via uvx):

{
  "mcpServers": {
    "netlens": {
      "command": "uvx",
      "args": ["netlens-mcp"]
    }
  }
}

Add either to your MCP client config (e.g. .mcp.json for Claude Code), then restart the session so the tools load.

Tools

web_search

Search the web and return real result links (title, URL, snippet), parsed locally — links, not summaries. Follow up with web_fetch to read a result.

The result reports which engine answered and what happened to any that were skipped, so falling through to a different backend is visible rather than silent:

{
  "query": "…",
  "engine": "mojeek",
  "results": [ … ],
  "engines_skipped": [ { "engine": "duckduckgo", "outcome": "HTTP 202" } ]
}

Outcomes are observations, not conclusions — HTTP 202 is what the server sent; whether that is throttling, changed markup or genuinely no matches cannot be determined from the response. With SearXNG configured, direct answers, infoboxes and suggestions appear alongside the results.

A search fetches a single result page (~10 results), returned in full by default so nothing at position 9/10 is dropped. There's no deep pagination — if the answer isn't in the first page, refine the query.

web_fetch

Fetch any page and return its full content as clean Markdown.

... View full README on GitHub