Skip to main content
Glama

Groundhog

Conformance Glama

Web search, read and research for AI agents — through a real, stealth-patched Chrome. Groundhog is an MCP server that finds pages, reads them, and researches across them, returning clean Markdown a model can trust: text no human could see is stripped by default before the model reads it, every source comes back with a provenance receipt, and a real browser reads pages that block plain fetchers — without the SSRF holes of naive fetch tools.

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

Quick start

Add Groundhog to your MCP client — that's it. On the first fetch, Groundhog pulls and starts the stealth-browser container for you (Docker or Podman required); no repo checkout, no manual steps. When the default (non-compose) auto-start path has to run, any stale container named groundhog-browser is removed first; a reachable browser is never touched.

Claude Code:

claude mcp add groundhog -- uvx groundhog-mcp

Claude Desktop / Cursor / Windsurf (claude_desktop_config.json or equivalent):

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

uvx fetches groundhog-mcp from PyPI on first run. The first fetch pulls the browser image (once, a few minutes); later fetches are instant. No container runtime? The status tool and any error say how to install one — or point CDP_URL at a hosted browser for zero-install use.

Prefer to manage the browser yourself? Start it and Groundhog will just use it:

docker run -d --rm --name groundhog-browser --shm-size 512m \
  -p 127.0.0.1:9222:9222 -- ghcr.io/dmytrome/groundhog:latest
# or, from a repo checkout: docker compose up --build -d
curl -s http://localhost:9222/json/version    # CDP is live

Set GROUNDHOG_AUTO_START_BROWSER=false to disable auto-start. To run the MCP server from source: cd mcp && uv sync && uv run groundhog-mcp.

All four tools are annotated readOnlyHint, which is what lets a client run them without a per-call confirmation. That describes what they do to your data: nothing is written, and no remote state is changed. Worth knowing, because it is the one exception: with auto-start on, the first call may pull and run the browser container, and remove an unreachable container named groundhog-browser first. A reachable one is never touched, and GROUNDHOG_AUTO_START_BROWSER=false turns the whole path off.

Related MCP server: firecrawl-mcp-server

What makes it different

  • Hidden text is stripped before the model reads it. Groundhog renders a real DOM, so it can judge what a human would actually see and strip what they could not, reporting each occurrence in threats. A strong heuristic, not a proof — see the limits of hidden-text detection. The eleven signals, the threats caveat and the include_hidden exception are documented under read_url.

  • Every source carries a receipt. SHA-256 hash of the extracted content, canonical URL, language, word count, and author/date when the page declares them — so a downstream claim traces back to exactly what was read. read_url returns the fetch time alongside it as fetched_at.

  • Safe by default. The SSRF guard resolves each host before navigating and refuses to return content from a URL that redirects into a private address. Read-only, with per-domain rate limiting. This matters most in research, where a third party chooses the URLs. See Security for the full blocklist and the guard's limits.

  • No automation tell. Puppeteer/Playwright/Selenium enable the CDP Runtime domain, which anti-bots detect (isAutomatedWithCDP). Groundhog drives the browser over raw CDP and never enables Runtime/Console, so that signal is absent — a clean session that full automation libraries can't produce over connect_over_cdp.

  • A real fingerprint. It's real Chrome, run headful under Xvfb (no HeadlessChrome token) — authentic TLS/HTTP2 fingerprint, real WebGL/canvas — not a Python HTTP client, so fingerprint-driven blocks go away and cheap proxies work where they otherwise wouldn't.

  • No model, no API key. research returns extracts, not summaries; your agent does the synthesis. Self-hosted and MIT — the pages you fetch never leave your infrastructure.

Tools

read_url(url, format="markdown", max_tokens=None, query=None, include_hidden=False)

Fetches a page and returns clean content plus provenance.

Key

Meaning

markdown

Extracted content (article-first, falls back to full text); format may be markdown or text

title

Page title

url

The URL you asked for

final_url

The URL after redirects (re-checked against the SSRF guard). Never rewritten: if the page's own final URL is unusable, the requested URL is reported and a final_url_suppressed threat says so

fetched_at

UTC ISO-8601 timestamp

status

What actually came back: ok, or challenge / blocked / rate_limited / not_found / server_error / unsupported_content when the content is not the page you asked for — so a Cloudflare interstitial, a 403, or a PDF is not read as if it were the real page. blocked covers 401/403 and every other 4xx that serves an error page (451, 400, 405…), with the exact code in http_status. unknown means no response — or no usable status — was observed for the document that was read: it is reported rather than assumed to be fine. A challenge is recognised from vendor mitigation markers — a header that exists only to announce it, or a request for an asset only a challenge loads — so it works whatever language the page is in; page wording is a last resort and only counts on a page too empty to be content. See the limits of block detection The verdict describes the document the text came from, so a page that redirects client-side (meta-refresh, location.href) is judged on where it landed, not where it started

http_status

The top-level response's HTTP status code, or null when it could not be observed

truncated

Whether the content was cut to fit the token budget

threats

Signals detected: hidden-CSS nodes and invisible-character classes; empty when none found

matches

When query is set: ranked passages with heading, offset, and score for citation

provenance

Content hash, canonical URL, language, word count, and author/date metadata when present

Because Groundhog renders a real DOM, it can evaluate computed styles. Text invisible to humans is stripped by default and each occurrence reported in threats with its signal type and a short excerpt: display:none/visibility:hidden, content-visibility: hidden (the subtree is skipped from layout while the element keeps an ordinary box, so no other signal sees it), opacity ≤ 0.05, font-size < 4 px, zero-size elements, an element that generates no box of its own (display: contents) whose contents render nothing, the sub-pixel box used by .sr-only/.visually-hidden accessibility utility classes (a pattern attackers now mimic), the legacy clip: rect(...) hiding technique, fully transparent text color, text color matching the background color (near-1:1 contrast), and elements positioned entirely outside the rendered page (e.g. left: -9999px). Non-trivial HTML comments are reported too — they never reach the extracted content either way, but a page embedding instructions this way is worth knowing about. A second, character-level class is stripped and reported alongside these: zero-width characters, bidi marks and RTL overrides, and the Unicode Tag block — an invisible ASCII mirror that is the canonical prompt-injection smuggling channel. Pass include_hidden=True to keep the stripped text in the output; threats is still populated so you know it was there.

Treat threats as untrusted. Entries come in six shapes (the character classes share one):

type

Carries

hidden_css

The hiding reason, an 80-char excerpt of the removed text, and the DOM location. All three are page-authored, so all three are stripped of invisible characters and length-capped — but they remain attacker-chosen text

zero_width / bidi / tag

A codepoint and count in reason, no excerpt. Detected on the text the page actually served — the extractor removes these characters on its way to Markdown, so scanning the extracted output would report none of them

report_truncated

How many entries were dropped when the cap was hit. Its own type, so it cannot be miscounted as a finding

final_url_suppressed

The page's own final URL was unusable (over-long, or carrying invisible characters) and was not returned; final_url reports the URL you requested instead

detection_degraded

The collector had to run in the page's own JavaScript world, where the page can replace the DOM APIs it uses. A short list proves nothing on that page

strip_incomplete

The rendered text was rebuilt from markup rather than read from layout. Either a flagged node could not be removed outright — it won the cascade against the hiding stylesheet (an inline !important does) or its recorded position did not resolve — or the page renders through open shadow roots, whose content has no layout to read. The second is by far the more common, and is routine rather than adversarial

The value of stripping is that the payload is out of the content being reasoned over, not that it is invisible to the model. At most 50 findings per page are returned (10 per source in research, since the fan-out multiplies the report); beyond that a report_truncated entry is appended stating how many were dropped, rather than truncating silently. The two classes are capped independently, so a page cannot bury the findings that carry its injection excerpt by flooding the report with decoys of the other kind. Notices are appended after the cap — so they can never themselves be dropped, and a capped list is up to 50 findings plus at most two notices.

Pass query to replace blunt head-truncation with relevance-ranked passage selection: content is chunked on markdown structure, ranked by lexical (BM25) relevance, and the top passages within the token budget are returned; matches gives each passage's heading, character offset, and score for downstream citation. Ranking runs on the sanitized content, so hidden-text injection payloads cannot influence which passages surface — with the one exception of include_hidden=True, which leaves the hidden text in the document and ranks it along with everything else.

search(query, limit=10)

Finds pages for a query and returns ranked hits — title, url, snippet, engine, score, published — plus the backend that answered. Hits are links only: nothing is fetched until you pass a URL to read_url.

Two backends, chosen automatically. Set SEARXNG_URL to use your own SearXNG instance (best results; needs formats: [html, json] in its settings.yml, since JSON is off by default upstream). With no instance configured, Groundhog renders a search page through the stealth browser instead — no extra infrastructure, at the cost of depending on that page's layout. Force one with GROUNDHOG_SEARCH_BACKEND=searxng|serp.

Every text field of a hit is attacker-influenceable — a poisoned page controls how it describes itself — so each passes through the same invisible-character stripping as page content, and each is length-capped. The URL is treated differently: it is what a model cites, so it is never rewritten. A hit is dropped outright if cleaning would change its URL at all, if that URL is not http/https, if it carries credentials, or if it exceeds 2048 characters. Both matter on the DuckDuckGo path, which percent-decodes the redirect wrapper and can therefore turn %E2%80%8B back into a real zero-width character inside the link. A backend that is unreachable, has JSON disabled, or whose every upstream engine is rate-limited raises an actionable error rather than reporting an empty web.

research(query, max_sources=5, max_tokens=None)

One call for "find out about X": searches, reads the top sources through the stealth browser, and returns the passages most relevant to query — ranked across all sources in a single pass, so a passage from source 4 competes fairly with one from source 1.

Returns passages (each with text, source_url, heading, score) and sources (each with url, title, status, page_status, threats, provenance). status is the fetch outcome (ok / blocked / timeout / error); page_status is what a page that loaded actually was — the same classification read_url reports, so a source that returned a bot-challenge or a non-HTML body is visible rather than passing as ok — and is null when the fetch never produced a page. A source whose page_status says its body is an interstitial or an error page contributes no passages: it would otherwise compete for your token budget against real content. It still appears in sources, saying why it contributed nothing. At most one page per registrable domain, for source diversity. Passages are extracts, not summaries — nothing is generated, and no model or API key is involved. When a passage isn't enough, read_url its source_url for the whole page.

A source that fails doesn't fail the call: it appears in sources with a status of blocked (SSRF guard), timeout, or error, so a partial answer is still usable and you can see what was missed. Because search results are chosen by a third party — and SEO-poisoned results are a documented in-the-wild attack — every fetched URL goes through the same SSRF guard and hidden-text stripping as read_url, and each source reports what was stripped from it. A source that failed carries provenance: null — only sources that were actually read are hashed. threats is per-source here and capped at 10 entries per source, lower than read_url's 50, because the fan-out multiplies it. max_sources is capped at 10.

It's slower than an API-backed research tool: a real browser renders every source. That's the trade for reading pages that block plain fetchers, and for being able to tell you what was hidden in them.

status()

Reports whether Groundhog can reach the stealth browser. Returns browser_reachable, cdp_url and a hint with remediation steps when it isn't reachable. The endpoint is reported as scheme, host and port only — a hosted browser often carries a credential in its URL, and this value reaches the model.

Configuration

MCP server (mcp/):

Env var

Default

Purpose

CDP_URL

http://127.0.0.1:9222

CDP endpoint of the stealth browser. May be remote (a DNS name or IP); auto-start is skipped for non-local values. The endpoint is unauthenticated — keep it on a private network or a tunnel.

GROUNDHOG_BLOCK_PRIVATE_IPS

true

Enforce the SSRF guard (resolve + block private ranges)

GROUNDHOG_MIN_DELAY_MS

5000

Minimum delay between requests to the same domain

GROUNDHOG_MAX_TOKENS

20000

Token budget before truncation

GROUNDHOG_MAX_CONCURRENT_PAGES

4

Cap on concurrent open tabs

SEARXNG_URL

(unset)

Your SearXNG instance for search, e.g. http://searxng:8080. Needs formats: [html, json]. Unset → SERP via the stealth browser.

GROUNDHOG_SEARCH_BACKEND

auto

auto (SearXNG when SEARXNG_URL is set, else SERP), or force searxng / serp

GROUNDHOG_AUTO_START_BROWSER

true

Auto-pull-and-run the browser container when it isn't reachable (needs Docker/Podman); false to manage it yourself

GROUNDHOG_BROWSER_IMAGE

ghcr.io/dmytrome/groundhog:latest

Image used for auto-start

GROUNDHOG_COMPOSE_FILE

(none)

Use docker compose -f <file> up -d for auto-start instead of docker run (local repo)

Dependencies: py3langid (which pulls in numpy) is used for language detection in the provenance result. It is installed in the MCP server package only — not in the browser container.

Browser container:

Env var

Default

Purpose

USER_AGENT

derived from installed Chrome

UA set at launch, so it is clean in every scope including workers

PROXY

(none)

Upstream proxy (http://user:pass@host:port); auth is relayed and timezone/locale auto-align to the exit IP

TZ

UTC

Fallback timezone; auto-derived from the exit IP when PROXY is set

WINDOW_SIZE

1920,1080

Initial Chrome window size

XVFB_WHD

1920x1080x24

Virtual display geometry

Under the hood: the stealth Chrome container

A minimal Docker container running headful Chrome under Xvfb with a remote CDP endpoint. Any CDP-speaking client (Puppeteer, Playwright, Selenium, chromedp, raw DevTools) can drive it — Groundhog is one such client.

  • Headful under Xvfb, not --headless=new — the browser reports Chrome, not HeadlessChrome, avoids headless-specific tells, and engages the real GPU path.

  • --disable-blink-features=AutomationControllednavigator.webdriver reads false.

  • UA set at launch from the installed Chrome version (USER_AGENT), so it is clean in every scope — main frame, network, and Web/Service Worker globals.

  • Proxy geo-coherence. When PROXY is set, the entrypoint geolocates the exit IP and aligns the browser timezone and locale to it — a timezone or locale that disagrees with the IP is itself a block signal. The country→locale table is CLDR likely-subtags. Chrome can't authenticate to a proxy over --proxy-server, so credentials are relayed through a local tinyproxy; WebRTC is pinned to the proxy path so the real IP can't leak.

  • GPU-aware WebGL. The entrypoint auto-detects a GPU (NVIDIA via the Container Toolkit, or Intel/AMD via /dev/dri) and uses hardware acceleration; without one it runs Mesa llvmpipe, a coherent software renderer that VMs and servers legitimately emit. See the gpus/devices hints in docker-compose.yml.

Verified results

Measured against a freshly built container (Chrome 149, headful under Xvfb, no proxy), driven over raw CDP:

Detector

Result

deviceandbrowserinfo

not a bot (isBot: false, zero flags)

browserscan

Normal

bot.sannysoft.com

31 / 31 checks pass

iphey is tracked informationally, not pass/fail: its one recurring flag is Location ("looks like you're trying to hide your location"), which fires on any datacenter/hosting exit IP regardless of browser fingerprint or TZ correctness — it passes on a residential IP and fails in CI (a cloud runner) and behind most proxies alike.

See RESULTS.md for the full live table (regenerated by tests/antibot.py and the Conformance workflow).

These reflect the raw-CDP client. Full automation libraries (Puppeteer/Playwright/Selenium) enable the CDP Runtime domain and are flagged as automated even against this container — see examples/ for which need patched (rebrowser) variants.

Examples

Client

Path

Puppeteer (Node)

examples/puppeteer

Playwright (Node)

examples/playwright-node

Playwright (Python)

examples/playwright-python

Selenium (Python)

examples/selenium-python

chromedp (Go)

examples/go-chromedp

Raw CDP (Python)

examples/python-raw-cdp

See examples/OTHER_TOOLS.md for crawl4ai, Scrapy + Playwright, go-rod, Crawlee, and nodriver pointers.

Security

The CDP endpoint is unauthenticated — anyone who can reach the port has full control of the browser. Bind it to localhost or a trusted private network; never expose it to the public internet. --no-sandbox is used because Chrome's sandbox does not work in an unprivileged container; keep the container isolated. To report a vulnerability, see SECURITY.md.

Limits of hidden-text detection

Worth knowing before treating an empty threats list as a clean bill of health. Nothing is removed from the live page — the markup is stripped inside a separate inert document, which is imported rather than cloned (cloneNode is itself [CEReactions]), and the rendered text comes from the live page with the flagged nodes hidden by an adopted stylesheet. So a page gets no synchronous hook to react to the strip. What that does not cover:

  • The style signals are thresholds, and the character set is a denylist. Those are the real limits — see below. The detector itself runs in an isolated world (Page.createIsolatedWorld), so a page cannot suppress it by replacing the DOM APIs it uses; if the browser ever declines to provide one, the result carries a detection_degraded threat rather than quietly weaker detection.

  • Thresholds can be sat just inside. opacity: 0.06, font-size: 4px, a contrast ratio just above 1.15 — all pass, as do hiding techniques the eleven signals don't model (clip-path, text-indent, transform: scale(0)).

  • Invisible-character coverage is a set, not a rule. Zero-width, bidi and the Unicode Tag block are stripped and reported; codepoints outside that set are not.

  • When the text is rebuilt, line breaks are guessed from tag names. In the two cases above the rendered text is taken from the stripped markup, which has no layout — so an element the page styled display:inline still gets a break, and a block-level tag outside the list gets none. Word boundaries are preserved; exact line structure is not.

  • Closed shadow roots are not read. Open ones are: their content is scanned for hidden text and composed into the output as the flat tree a reader sees, slots included. A closed root is unreachable from the isolated world, so it cannot be scanned — and what cannot be scanned is not composed in. Its content stays out of the result entirely rather than arriving unexamined.

  • A page can win the cascade against the hiding sheet, or hide its own <body>. An inline !important beats an author stylesheet, and innerText returns raw text when nothing renders at all. In either case the rendered text is abandoned for the stripped markup, which is a weaker guarantee than reading real layout — reported as strip_incomplete rather than left to look like a clean strip.

Limits of block detection

status tells you a fetch returned a challenge or an error page rather than the content you asked for. Worth knowing what it does and does not cover.

  • Mitigation markers are a list, and the list is not exhaustive. A challenge is called with certainty when the response carries a header that exists only to announce it (cf-mitigated, x-vercel-mitigated, x-amzn-waf-action, x-dd-b, x-datadome-cid) or when the page requests an asset only a challenge loads (Cloudflare's orchestrator, DataDome, PerimeterX, Imperva). A vendor absent from that list, or one that changes its endpoint, falls through to the weaker signals below.

  • The wording fallback is English, and only fires on an empty page. A challenge with no recognised marker is caught only if it renders almost no text and matches a known phrase. A localized interstitial from an unlisted vendor is the gap — it is why the markers exist, and why they are preferred over any amount of phrase tuning.

  • A soft block is undetectable here. A page that returns 200 with a plausible body but the data quietly withheld looks exactly like content. Nothing in this classification sees it; only comparing against what the page should contain would.

  • unknown is not ok. It means no response, or no usable status, was observed for the document that was read. It is reported rather than assumed fine, and it is not treated as a block — a source carrying it still contributes passages in research.

  • Vendor presence is not a block. server: cloudflare, cf-ray and __cf_bm are on a large share of the web on every page it serves normally, so they are deliberately not used; nor is cf_clearance, which is issued when a challenge is passed.

What the SSRF guard blocks. Each host is resolved and rejected if it lands in loopback, RFC-1918 private, link-local (incl. 169.254.169.254), reserved, multicast, unspecified, CGNAT 100.64.0.0/10, or IPv4-mapped IPv6 ranges. Only http and https are allowed, and credentials in URLs are rejected. The check runs again immediately before navigation, and once more against final_url after redirects.

Limits of the SSRF guard. It is a strong default, not a sandbox. Know these before pointing it at untrusted URLs:

  • The guard resolves and checks the host before navigation and re-checks final_url after the page loads. A redirect into a private address is therefore still requested by Chrome — its content is never returned, but a blind SSRF or a state-changing internal GET has already landed. Intermediate hops in a longer redirect chain are not individually checked.

  • Sub-resource requests the page itself issues (img, script, iframe, fetch) are not intercepted; only the top-level navigation is checked.

  • Groundhog resolves DNS in its own process while Chrome resolves independently at navigate time, so a short-TTL rebinding window remains open. Closing these properly needs request-level interception (CDP Fetch).

  • Fetches share the browser's default profile — targets are created without a separate browser context — so cookies and storage set by one page persist into later fetches. "Read-only" describes Groundhog's own API, not the JavaScript on a fetched page, which can issue requests of its own from that shared profile.

Set GROUNDHOG_BLOCK_PRIVATE_IPS=false only on a network where reaching internal addresses is intended.

A note on "stealth"

Best-effort, not a guarantee. It defeats common open-source detectors and lets cheap proxies work on many mid-tier targets, but it does not beat sophisticated commercial anti-bot systems that gate on IP reputation, TLS/HTTP2 fingerprints, and behavioral analysis. Use it for legitimate, authorized automation and testing.

Privacy Policy

Groundhog is self-hosted software, not a service. It runs on your machine, and the project operates no servers that it talks to.

What is collected: nothing. There is no telemetry, no analytics, no crash reporting and no licence check. The maintainers receive no data about you, the URLs you fetch, or the content you read. There is no account to create.

How data is used and stored. Pages are fetched by a browser running on your own machine and returned to the MCP client that asked for them. The server keeps no database, writes no logs to disk, and persists nothing between calls — with one exception worth knowing: fetches share the browser container's profile, so cookies and storage set by one fetched page remain in that container and are visible to later fetches. Removing the container discards them (docker rm -f groundhog-browser), and the container is removed automatically if you started it with --rm.

Third parties your traffic reaches. Only those you direct it to, plus two you should know about:

  • The sites you fetch, which see the request as an ordinary browser visit from your IP — or from your proxy's exit IP if PROXY is set.

  • The search backend. With SEARXNG_URL set, your queries go to the SearXNG instance you chose. Without it, search renders a public search engine's results page through the browser, so that engine sees the query.

  • An IP-geolocation lookup, only when PROXY is set. The container asks an external service for the proxy exit IP's country so it can align the browser's timezone and locale. That request carries the exit IP and nothing else. It does not happen without a proxy.

  • PyPI and GHCR at install time, to download the package and browser image.

Retention. Nothing is retained by the project. On your machine, the browser container holds cookies and cache for its lifetime; deleting the container deletes them.

Contact. Questions and security reports: SECURITY.md, or open an issue at https://github.com/dmytrome/groundhog/issues.

License

MIT

Available Tools

4 tools
read_urlRead a URLA
Read-only

Fetch one web page through the stealth browser and return clean, grounded content with provenance.

Hidden text injected for models but invisible to humans is stripped by default and reported in threats. Use this to ground answers in live web content, including sites that block plain fetchers.

Reads a URL you already have: use search to find URLs, or research to search and read in one call. Fetches are rate limited per domain (5s apart by default), so several pages from one site are not instant.

ParametersJSON Schema
NameRequiredDescriptionDefault
urlYesAbsolute http(s) URL. Private and loopback addresses are refused.
queryNoWhen set, `matches` carries the passages most relevant to it, each with its heading and offset for citation.
formatNo'markdown' extracts the article; 'text' returns the page's rendered text.markdown
max_tokensNoToken budget for the content. Omit to use the server's GROUNDHOG_MAX_TOKENS (20000 by default). Must be positive.
include_hiddenNoKeep text that is invisible to a human reader. It is reported in `threats` either way; this only controls whether it stays in the content.

Output Schema

ParametersJSON Schema
NameRequiredDescription
urlYes
titleYes
statusYes
matchesYes
threatsYes
markdownYes
final_urlYes
truncatedYes
fetched_atYes
provenanceYes
http_statusYes

TDQS

A4.3/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint=true and openWorldHint=true, so the safety profile is covered. The description adds meaningful behavioral context beyond annotations: hidden-text stripping with threat reporting, stealth-browser fetching for blocked sites, and per-domain rate limiting. It does not contradict annotations. The only minor gap is no mention of failure modes or what 'grounded content with provenance' structurally looks like, though the output schema likely covers return shape.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three tight paragraphs, each earning its place: first defines the action and output, second explains the hidden-text safety behavior and value proposition, third gives usage guidance, alternatives, and rate-limit caveat. It's appropriately sized for a tool with 5 parameters and meaningful behavioral nuance, though it leans slightly long relative to its sibling-differentiation needs.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With an output schema present, return-value details are handled structurally. The description covers the tool's distinctive behaviors (stealth fetching, hidden-text stripping, provenance), usage guidance, rate limits, and alternatives. For a tool of moderate complexity with rich schema and annotations, the description is complete enough. It could add slightly more on error/failure behavior, but it is not a material gap.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so all five parameters are documented in the schema. The description resists repeating schema detail and instead adds cross-parameter context (e.g., 'reported in `threats`' ties include_hidden and hidden-text stripping together). The `query` and `format` behaviors become clearer through the description's grounding framing, but the schema already does the heavy lifting. Baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb+resource ('Fetch one web page through the stealth browser') and clearly states what it returns ('clean, grounded content with provenance'). It explicitly differentiates from siblings: 'use `search` to find URLs, or `research` to search and read in one call', naming the alternatives directly. The reference to 'sites that block plain fetchers' adds a clear use-case distinction.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly states when to use this tool vs alternatives: 'Reads a URL you already have: use search to find URLs, or research to search and read in one call.' It also discloses the rate-limiting behavior ('5s apart by default'), setting expectations about latency. This is explicit when/alternative guidance with concrete operational context.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

researchResearch the webA
Read-only

Search the web and return ranked passages drawn from several sources.

One call does what search + repeated read_url would: finds pages, reads them through the stealth browser, and returns the passages most relevant to query — each attributed to its source, with that source's provenance receipt and any stripped injection payloads. A source that fails is reported in sources rather than failing the whole call.

Prefer read_url when you already have the URL, and search when you only want links. This reads max_sources pages, rate limited per domain, so it is the slowest of the three and the one to avoid for a single known page.

ParametersJSON Schema
NameRequiredDescriptionDefault
queryYesThe question to research. Passages are ranked against it.
max_tokensNoToken budget for the returned passages. Omit to use the server's GROUNDHOG_MAX_TOKENS (20000 by default). Must be positive.
max_sourcesNoHow many pages to read. Values outside 1-10 are clamped rather than rejected. Each source is a full page fetch, so this is the main cost and latency control.

Output Schema

ParametersJSON Schema
NameRequiredDescription
queryYes
backendYes
sourcesYes
passagesYes
truncatedYes

TDQS

A4.7/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint=true and openWorldHint=true, and the description adds meaningful behavioral context: that it reads through a stealth browser, returns provenance receipts, strips injection payloads, and reports failed sources in `sources` rather than failing the whole call. This adds real behavioral value beyond the annotations, though return format specifics could be further detailed beyond what the output schema shows.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three paragraphs, each earning its place: what it does, how failures are handled, and when to use alternatives. No wasted words, well front-loaded with the purpose sentence.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a complex tool with an output schema and good annotations, the description covers usage differentiation, failure semantics, cost/latency control, and behavioral traits. An output schema exists so return values needn't be spelled out. Highly complete for its complexity.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the schema documents all three parameters. The description adds value by explaining max_sources is the main cost/latency control and that values outside 1-10 are clamped, and that max_tokens has a server default (GROUNDHOG_MAX_TOKENS). It supplements but doesn't fully compensate the structured schema since the schema is already rich.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb (research/search) plus resource (the web), and clearly differentiates from siblings by noting this combines `search` + repeated `read_url` into one call. The distinction from read_url and search is explicit.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Gives explicit when-to-use guidance: prefer `read_url` when you already have the URL, `search` when you only want links. Also warns this is the slowest of the three due to rate limiting per domain, and should be avoided for a single known page. This is model-tier guidance naming alternatives and exclusions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

statusBrowser statusA
Read-only

Check whether Groundhog can reach the stealth browser. Call this to diagnose setup before fetching: if browser_reachable is false, follow hint to start the browser, then retry.

ParametersJSON Schema
NameRequiredDescriptionDefault

No parameters

Output Schema

ParametersJSON Schema
NameRequiredDescription
hintYes
cdp_urlYes
browser_reachableYes

TDQS

A4.7/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description names the specific output field `browser_reachable` and the `hint` field, giving the agent concrete knowledge of what to expect. Annotations (readOnlyHint=true) already signal this is a safe read operation. The description adds value by explaining what the output means behaviorally (telling the agent what to do when unreachable), going beyond the annotation safety profile.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences, front-loaded with the core purpose first, followed by actionable diagnostics. No wasted words. Slight deduction could be argued for not being maximally compact, but the conditional instruction earns its place since it directly guides agent behavior. Efficient and purposeful.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

This is a simple, parameterless diagnostic tool with an output schema present, so the description doesn't need to explain return values extensively. The description covers the purpose, when to use it, and the conditional action to take based on the result. For a tool of this complexity, this is complete — nothing meaningful is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has 0 parameters, so there is no parameter meaning to convey — the schema itself documents this fully (100% coverage by definition since there are no params). The task is parameter-free, so a baseline of 4-5 applies, and the description fully compensates by explaining what the tool checks and what its output communicates.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: checking whether Groundhog can reach the stealth browser. It uses a specific verb ('check') with a clear resource ('reach the stealth browser') and includes a diagnostic framing, distinguishing it from sibling tools (read_url, research, search) which are substantive data-gathering operations rather than setup diagnostics.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives explicit when-to-use guidance: 'Call this to diagnose setup before fetching.' It also provides conditional follow-up instructions: if `browser_reachable` is false, follow `hint` to start the browser, then retry. This is directly actionable and tells the agent exactly the workflow to follow.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. 2 tool updatesv0.10.0
    • Changedread_url3 fields changed
      • addedOutput schema / properties / http_status
        Added value: +{
        +  "anyOf": [
        +    {
        +      "type": "integer"
        +    },
        +    {
        +      "type": "null"
        +    }
        +  ],
        +  "title": "Http Status"
        +}
      • addedOutput schema / properties / status
        Added value: +{
        +  "enum": [
        +    "ok",
        +    "challenge",
        +    "blocked",
        +    "rate_limited",
        +    "not_found",
        +    "server_error",
        +    "unsupported_content",
        +    "unknown"
        +  ],
        +  "title": "Status",
        +  "type": "string"
        +}
      • changedOutput schema / required
        Previous value: -[
        -  "markdown",
        -  "title",
        -  "url",
        -  "final_url",
        -  "fetched_at",
        -  "truncated",
        -  "threats",
        -  "matches",
        -  "provenance"
        -]New value: +[
        +  "markdown",
        +  "title",
        +  "url",
        +  "final_url",
        +  "fetched_at",
        +  "status",
        +  "http_status",
        +  "truncated",
        +  "threats",
        +  "matches",
        +  "provenance"
        +]
    • Changedresearch2 fields changed
      • addedOutput schema / $defs / Source / properties / page_status
        Added value: +{
        +  "anyOf": [
        +    {
        +      "enum": [
        +        "ok",
        +        "challenge",
        +        "blocked",
        +        "rate_limited",
        +        "not_found",
        +        "server_error",
        +        "unsupported_content",
        +        "unknown"
        +      ],
        +      "type": "string"
        +    },
        +    {
        +      "type": "null"
        +    }
        +  ],
        +  "title": "Page Status"
        +}
      • changedOutput schema / $defs / Source / required
        Previous value: -[
        -  "url",
        -  "title",
        -  "status",
        -  "threats",
        -  "provenance",
        -  "error"
        -]New value: +[
        +  "url",
        +  "title",
        +  "status",
        +  "page_status",
        +  "threats",
        +  "provenance",
        +  "error"
        +]
  2. 3 tool updatesv1.0.0
    • Changedread_url5 fields changed
      • addedInput schema / properties / format / description
        Added value: +"'markdown' extracts the article; 'text' returns the page's rendered text."
      • addedInput schema / properties / include_hidden / description
        Added value: +"Keep text that is invisible to a human reader. It is reported in `threats` either way; this only controls whether it stays in the content."
      • addedInput schema / properties / max_tokens / description
        Added value: +"Token budget for the content. Omit to use the server's GROUNDHOG_MAX_TOKENS (20000 by default). Must be positive."
      • addedInput schema / properties / query / description
        Added value: +"When set, `matches` carries the passages most relevant to it, each with its heading and offset for citation."
      • addedInput schema / properties / url / description
        Added value: +"Absolute http(s) URL. Private and loopback addresses are refused."
    • Changedresearch3 fields changed
      • addedInput schema / properties / max_sources / description
        Added value: +"How many pages to read. Values outside 1-10 are clamped rather than rejected. Each source is a full page fetch, so this is the main cost and latency control."
      • addedInput schema / properties / max_tokens / description
        Added value: +"Token budget for the returned passages. Omit to use the server's GROUNDHOG_MAX_TOKENS (20000 by default). Must be positive."
      • addedInput schema / properties / query / description
        Added value: +"The question to research. Passages are ranked against it."
    • Changedsearch2 fields changed
      • addedInput schema / properties / limit / description
        Added value: +"How many hits to return. Values outside 1-25 are clamped rather than rejected."
      • addedInput schema / properties / query / description
        Added value: +"What to search for. Must not be empty."
  3. 4 tool updates
    • First observedread_url
    • First observedresearch
    • First observedsearch
    • First observedstatus

TDQS

A4.3/5.0
Disambiguation4/5

The four tools have mostly distinct purposes: read_url reads a known URL, search returns links only, research does search+read combined, and status is a diagnostic check. Statatus is clearly separate. The main potential confusion is between read_url and research, but the descriptions explicitly clarify when to use each (read_url for known URLs, search for links only, research for combined search+read), which mitigates overlap well.

Naming Consistency4/5

Tool names use consistent, short lowercase verbs (read_url, research, search, status) with an underscore pattern for read_url. The naming is predictable and readable. Minor deviation: research is a compound concept rather than a verb_noun pair, but this is a minor stylistic point since all names are lowercase, consistent verbs.

Tool Count4/5

At 4 tools, this is a lean set that covers the core web-research workflow: status (diagnose), search (find URLs), read_url (read one page), research (combined find+read). Each tool serves a clear purpose with minimal redundancy. Slightly thin but appropriately scoped for a focused browser/search server.

Completeness3/5

The server covers the core browse/search lifecycle well: diagnose, search, read, and combined research. However, there are gaps such as no way to extract or transform content beyond returning passages, no pagination or follow-up operations, and no direct way to get raw content or handle specific output formats. The core workflow (search-then-read) is complete, but deeper research needs are not addressed.

Maintenance

ActivityMaintained
ResponsivenessSyncing

Related MCP Connectors

Related MCP Servers

  • A
    license
    A
    quality
    C
    maintenance
    A Model Context Protocol (MCP) server implementation that integrates with FireCrawl for advanced web scraping capabilities.
    26
    40,139
    7,395
    MIT
  • A
    license
    A
    quality
    C
    maintenance
    Enables web content extraction, screenshot capture, web search, arXiv paper search, and image search through Jina AI's APIs. Provides tools for reading URLs as markdown, searching the web for current information, and finding academic papers or images.
    19
    840
    Apache 2.0

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/dmytrome/groundhog'

If you have feedback or need assistance with the MCP directory API, please join our Discord server