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PopNx MCPMCP servers for people who use AI · explained in plain words

Groundhog

by dmytromeversion 0.22.0i★ –iRuns on your computer
Registry nameio.github.dmytrome/groundhog-mcp

Install

Overview

Description from the maker (original English)

Search, read and research the web, with hidden text stripped by default and sources hashed

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

  • Connection: Runs on your computer
  • Transport: stdio
  • Category: Search & AI memory

Install

Pick the AI app you use, then copy the settings.

Before you install

  • Basic checks: 1 of 1 passed
  • Runs on your computer with your user’s permissions (files, network, apps).
  • The registry lists no key to fill in.

You need

  • PyPIPython’s uv installed (for the uvx command)

Which app do you use?

Pick your app above. We remember it, so next time the button says “Install in …”.

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

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

Run this in your terminal

claude mcp add groundhog -- uvx groundhog-mcp

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

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

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "groundhog": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "groundhog-mcp"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.

Your choice stays on this device in a cookie; no account needed.

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 8, 2026

  • ✓ Pass

    Maker matches the repo

    The registry name was verified with the GitHub account dmytrome, which owns the repo

  • … Not checked yet

    Still maintained

    We have not read this repo from GitHub yet

  • … Not checked yet

    Has a licence

    We have not read this repo from GitHub yet

  • – Not applicable

    Endpoint responds

    This one runs on your computer; there is no internet endpoint

  • – Not applicable

    Sign-in with OAuth

    Runs on your computer and uses local settings instead

  • … Not checked yet

    No hidden instructions in tool descriptions

    Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Search & AI memoryi

  • More stars than 0% of the other 5717 servers in this category
  • Published to the registry more recently than 74% of the other 5717 servers in this category
  • Basic checks equal to or better than 100% of the other 5717 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is Groundhog safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

The registry does not list a required key, though some servers ask you to sign in on first use.

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed –, and the latest version (0.22.0) reached the registry 13 days ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Python (uv) on your computer.

What can I use instead?

In the same category: Context7, Codebase Memory, Exa

Alternatives

Servers in the same category from other makers, sorted by stars.

Reading a card:↓ Downloads per weeki★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

Context7

Feeds AI the latest docs for libraries and frameworks before it answers, so code it writes does not use outdated, removed functions.

by upstashWidely used↓ 972.7K/wk★ 64.2KUpdated 2 days ago

Computer or cloud

Codebase Memory

Codebase knowledge graph for AI agents — 162 languages, sub-ms queries, 99% fewer tokens.

by DeusDataWidely used↓ 18K/wk★ 48.1KUpdated 22 days ago

Runs on your computer

Exa

Connect AI agents to Exa for web search, content fetching, and multi-step research.

by exa-labsWidely used★ 5.2KUpdated 2 months ago

Runs in the cloud✓ exa.ai

README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

Groundhog

Web search, read and research for AI agents, through a real, stealth-patched Chrome. Groundhog is an MCP server that returns clean Markdown a model can trust: text no human could see is stripped before the model reads it and reported, every source comes with a provenance receipt, and a real browser reads pages that block plain fetchers.

agent / crawler  ──MCP──▶  Groundhog (search, read_url, research)  ──CDP──▶  stealth Chrome  ──▶  the web

Measured against other fetch layers

Twenty-eight pages carry text a human can't see, and three controls carry none. A case passes when the payload doesn't reach the model and the article text still does.

containedkept the articlereported itfalse positives
requests + trafilatura25/2828/280/280/3
Scrapling (HTTP)16/2828/280/280/3
Jina Reader15/2828/280/280/3
Firecrawl7/2828/280/280/3
Groundhog28/2828/2825/280/3

Other extractors often drop hidden text by accident, but none of them tells the caller anything was removed. The three cases Groundhog doesn't report (a hidden input value, a meta description, an iframe srcdoc) never reach any extractor. The corpus is public at dmytrome.github.io/groundhog; the harness and its limits are in benchmark/.

Quick start

Claude Code:

claude mcp add groundhog -- uvx groundhog-mcp

Claude Desktop, Cursor, Windsurf:

{

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

On the first fetch Groundhog starts the Chrome you already have, headless, in its own profile at ~/.groundhog/chrome. Your own browsing, tabs and logins are never touched. If Chrome is missing, status and the error say what to install.

GROUNDHOG_BROWSER=stealth runs the hardened browser container instead (Docker or Podman; the first pull takes a few minutes). To run it yourself:

docker run -d --rm --name groundhog-browser --shm-size 512m \

-p 127.0.0.1:9222:9222 -- ghcr.io/dmytrome/groundhog:latest

CDP_URL points Groundhog at any browser and is used as given: http:// is probed for /json/version, ws:// or wss:// (what hosted browsers hand out) is connected to directly. Auto-start only runs for a local address that isn't answering, and GROUNDHOG_AUTO_START_BROWSER=false turns it off. From source: cd mcp && uv sync && uv run groundhog-mcp.

All four tools are annotated readOnlyHint: they write nothing and change no remote state. The one side effect is auto-start, which may launch Chrome or, with stealth, run the container after removing an unreachable one named groundhog-browser.

What makes it different

  • Hidden text is stripped and reported. A rendered DOM shows what a human would see; everything else goes, and each removal is listed in threats. It's a strong heuristic, not a proof: see the limits.
  • Every source carries a receipt: a SHA-256 of the extracted content, canonical URL, language, word count, and author and date when the page declares them.
  • Safe by default. An SSRF guard checks every document request, redirects and frames included, with per-domain rate limiting. See Security.
  • No automation tell. Groundhog drives Chrome over raw CDP and never enables the Runtime domain that anti-bots detect in Puppeteer, Playwright and Selenium.
  • A real fingerprint. Real Chrome means real TLS, HTTP/2, WebGL and canvas. In headless mode the HeadlessChrome token is replaced and client hints are copied from the browser; shared and service workers aren't covered. The stealth image runs headful under Xvfb.
  • No model, no API key. research returns extracts and your agent does the synthesis.

Tools

read_url(url, format="markdown", max_tokens=None, query=None, include_hidden=False)
KeyMeaning
markdownExtracted content, article first, falling back to the rendered text inside a code fence, so none of it reads as markdown; a PDF comes back as one ## Page N section per page with its text fenced. format may be markdown or text
titlePage title
urlThe URL you asked for
final_urlThe URL after redirects, re-checked by the SSRF guard. If unusable, the requested URL is reported with a final_url_suppressed threat
fetched_atUTC ISO-8601 timestamp
statusok, or challenge / blocked / rate_limited / not_found / server_error / unsupported_content when what came back isn't the page you asked for. blocked covers 401, 403 and other 4xx error pages. too_large means the page had over 5 MiB of HTML or 2 MiB of text, or was a PDF over 10 MiB, 100 pages or 20 seconds of parsing, and nothing of it is returned. An encrypted or malformed PDF is unsupported_content. empty means the rendered page showed no text a reader would see (text in closed shadow roots, iframes and alt attributes doesn't count), whatever markdown holds. With include_hidden, text hidden by styling counts as shown; invisible characters never do. unknown means no usable status was observed. Judged on the document the text came from, after client-side redirects
http_statusThe top-level HTTP status, or null
truncatedWhether the token budget cut the content
threatsWhat was stripped; empty when nothing was found
matchesWith query: ranked passages with id, heading, offset, end, score and clamped (cut short to fit max_tokens). offset and end index the page's full markdown, and that span is the text returned; a piece of a long code block comes back with its fence lines added around it. Code is never cut mid-piece: a matching code block or piece larger than max_tokens is left out, and when nothing fits markdown is empty with truncated set, so raise max_tokens
set_asideWith query: scoring passages the relevance floor dropped
provenanceContent hash, canonical URL, language, word count, author and date

Stripped by default: display:none, visibility:hidden, content-visibility:hidden, opacity ≤ 0.05, font-size < 4px, zero-size and display:contents boxes that render nothing, .sr-only-style sub-pixel boxes, clip: rect(...), a clip-path that leaves nothing (circle(0), inset(100%), a polygon on one line), transform: scale(0) on either axis, a filter whose opacity is 0.05 or less, zero-height or zero-width boxes that clip their overflow, transparent or background-coloured text, off-page positioning, collapsed , content, and zero-width, bidi and Unicode Tag characters. A box whose only text is an open popover or modal dialog is kept, because that dialog still shows on screen; any other text in the box is stripped as usual. HTML comments are reported too. In a PDF, text drawn in render mode 3 or 7, which paints nothing, is stripped and reported as hidden_pdf. That includes the OCR layer of a scanned page, so a scan whose only text is that layer is empty unless you pass include_hidden. include_hidden=True keeps the text but still reports it. alt, aria-label, aria-description and title text never appears in markdown or the rendered text; values of 125 characters or more are reported as hidden_attribute with a capped excerpt, because long text there is a known carrier.

Treat threats as untrusted: its excerpts are page-authored text, cleaned and length-capped.

typeCarries
hidden_cssThe hiding reason, an 80-character excerpt and the DOM location
hidden_attributeThe same, for text in an alt, aria-label, aria-description or title attribute
hidden_templateThe same, for text inside a
hidden_pdfThe same, for text a PDF drew invisibly, with the page as its location
zero_width / bidi / tagA codepoint and count in reason, detected on the served text
report_truncatedHow many entries the cap dropped
final_url_suppressedThe page's final URL was unusable and not returned
detection_degradedDetection ran in the page's own JavaScript world, which the page can tamper with
strip_incompleteThe text was rebuilt from markup rather than layout, usually because of open shadow roots

At most 50 findings per page are returned (10 per source in research), with the two classes capped separately so decoys can't bury a real payload. Notices are appended after the cap.

query swaps head-truncation for BM25 passage ranking on the sanitized content, keeping passages within half the best score up to the budget.

search(query, limit=10)

Returns hits (title, url, snippet, engine, score, published) and the backend that answered. Nothing is fetched. With SEARXNG_URL set it uses your SearXNG instance, which needs formats: [html, json]; otherwise it renders a search page through the browser. Hit text is cleaned and capped, and a hit whose URL would change under cleaning, isn't http(s), carries credentials or exceeds 2048 characters is dropped. A backend that can't answer raises an error instead of returning an empty web.

research(query, max_sources=5, max_tokens=None, include_domains=None, exclude_domains=None, published_after=None, aim=None, follow=None)

Searches, reads the top sources and ranks passages from all of them in one pass.

  • passages: id, text, source_url, heading, score, start, end, clamped, fence. text is exactly markdown[start:end]; clamped says it was cut short to fit the budget. A code block is never cut short, only left out. A passage cut from a long code block carries the block's opening line in fence: reopen with it when text doesn't start with it, and close the block when text doesn't end with a closing fence. id stays stable while the page doesn't change.
  • sources: url, title, status (ok / blocked / timeout / error), page_status (as in read_url), threats, threat_total, threat_counts (every finding by type, spans the page's detector dropped as hidden_unclassified), provenance, filtered, depth and discovered_via (the candidate it was followed from, with your why). A failed source doesn't fail the call. A challenge, an error page, an empty page or any page whose markdown is blank counts as not_content and contributes no passages.
  • One page per registrable domain unless include_domains is set, and then no more pages per site than GROUNDHOG_MAX_CONCURRENT_PAGES; max_sources goes up to 10.

include_domains reads only those domains and their subdomains, exclude_domains never reads them, and published_after (YYYY-MM-DD) drops pages dated earlier. Up to 8 domains can be included and 50 excluded. A page that redirects into an excluded domain or out of the included ones, is dated too early, or repeats the URL or text of a page already used is listed with filtered and contributes no passages. The query sent to the engine names at most eight domains; further excluded ones are filtered after the search. aim (up to 200 characters) says what the evidence must show and is echoed back without changing the search or the ranking.

receipt holds the executed_query, the distinct hits and hits_by_domain, the hits not fet

Only the beginning is shown; read the rest in the repo

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