Context7
Up-to-date docs for AI agents
Beschreibung vom Entwickler (englisches Original)
Search, read and research the web, with hidden text stripped by default and sources hashed
Diese drei werden nie zu einer Punktzahl zusammengefasst: Meinungen, Messungen und Beliebtheit sind verschiedene Dinge.
Für diesen Server haben wir noch keine Zusammenfassung in einfacher Sprache geschrieben. Unten stehen die Fakten, die wir aus der Registry gelesen haben.
Wähle die KI-App, die du nutzt, und kopiere die Einstellungen.
Du brauchst
Welche App nutzt du?
Wähle oben deine App. Wir merken sie uns, damit der Button beim nächsten Mal „In … installieren“ anzeigt.
Öffne Claude Desktop → Settings → Developer → Edit Config und füge dies in claude_desktop_config.json ein
{
"mcpServers": {
"groundhog": {
"command": "uvx",
"args": [
"groundhog-mcp"
]
}
}
}Führe das in deinem Terminal aus
claude mcp add groundhog -- uvx groundhog-mcpIn .cursor/mcp.json in deinem Projekt oder in ~/.cursor/mcp.json einfügen
{
"mcpServers": {
"groundhog": {
"command": "uvx",
"args": [
"groundhog-mcp"
]
}
}
}Dein Browser fragt, ob er die App öffnen darf, dann zeigt die App die Einstellungen und bittet dich um Bestätigung. Schlüsselwerte bleiben leer, damit du sie selbst einträgst.
In .vscode/mcp.json in deinem Projekt einfügen
{
"servers": {
"groundhog": {
"type": "stdio",
"command": "uvx",
"args": [
"groundhog-mcp"
]
}
}
}Dein Browser fragt, ob er die App öffnen darf, dann zeigt die App die Einstellungen und bittet dich um Bestätigung. Schlüsselwerte bleiben leer, damit du sie selbst einträgst.
Dieser Server läuft auf deinem Computer, und ChatGPT kann sich nur mit Servern im Internet verbinden. Wähle eine andere App.
Deine Auswahl bleibt in einem Cookie auf diesem Gerät; kein Konto nötig.
Diese Einstellungen werden aus dem Registry-Eintrag des Entwicklers erzeugt. Wenn in der README etwas anderes steht, folge der README.
Läuft auf deinem Computer; die Tool-Liste erscheint nach der Installation in deiner KI-App.
Wir prüfen Informationen, die jeder sehen kann; den Code haben wir nicht gelesen. Checks, die nicht zutreffen, werden nicht mitgezählt. · Geprüft am 7. Nov. 2026
Der Registry-Name wurde mit dem GitHub-Konto dmytrome bestätigt, dem das Repo gehört
Dieses Repo haben wir noch nicht von GitHub gelesen
Dieses Repo haben wir noch nicht von GitHub gelesen
Dieser Server läuft auf deinem Computer; es gibt keinen Endpunkt im Internet
Läuft auf deinem Computer und nutzt stattdessen lokale Einstellungen
Läuft auf deinem Computer; Tool-Listen können wir nur von Endpunkten im Internet lesen
Verglichen mit allen aktiven Servern dieser Kategorie in der Registry. Sterne zählen nur, wenn dem Herausgeber das Repo gehört.
Er hat 1 von 1 zutreffenden Basischecks bestanden. Den Code haben wir nicht gelesen. Bevor du einen Schlüssel oder Token hinzufügst, sieh nach, welche Zugriffe der Server verlangt, und nutze einen Schlüssel, der nur die Berechtigungen hat, die du brauchst.
Die Registry nennt keinen erforderlichen Schlüssel, manche Server bitten dich aber bei der ersten Nutzung, dich anzumelden.
Er läuft auf deinem Computer. Deine KI-App startet ihn bei Bedarf, und die Daten laufen nicht über die Server des Entwicklers (außer der Server ruft selbst einen Onlinedienst auf).
Das GitHub-Repo wurde zuletzt – geändert, und die neueste Version (0.22.0) kam vor 12 Tagen in die Registry.
Apps, die MCP unterstützen, etwa Claude Desktop, Claude Code, Cursor und VS Code. Außerdem brauchst du Python (uv) auf deinem Computer.
In derselben Kategorie: Context7, Codebase Memory, Exa
Server derselben Kategorie von anderen Entwicklern, sortiert nach Sternen.
So liest du eine Karte:★ GitHub-SterneiDrei Säulen: Bewertungen · Checks · NutzungiAktualisiert = neueste Version in der Registry veröffentlichti
Up-to-date docs for AI agents
Codebase knowledge graph for AI agents — 162 languages, sub-ms queries, 99% fewer tokens.
Connect AI agents to Exa for web search, content fetching, and multi-step research.
Unverändert aus dem Repo des Entwicklers übernommen. PopNx MCP hat den Inhalt weder geprüft noch empfiehlt es ihn. HTML, Bilder und Skripte wurden entfernt. Links führen von dieser Website weg.
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
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.
| contained | kept the article | reported it | false positives | |
|---|---|---|---|---|
requests + trafilatura | 25/28 | 28/28 | 0/28 | 0/3 |
| Scrapling (HTTP) | 16/28 | 28/28 | 0/28 | 0/3 |
| Jina Reader | 15/28 | 28/28 | 0/28 | 0/3 |
| Firecrawl | 7/28 | 28/28 | 0/28 | 0/3 |
| Groundhog | 28/28 | 28/28 | 25/28 | 0/3 |
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/.
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.
threats. It's a strong heuristic, not a proof: see the limits.Runtime domain that anti-bots detect in Puppeteer, Playwright and Selenium.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.research returns extracts and your agent does the synthesis.read_url(url, format="markdown", max_tokens=None, query=None, include_hidden=False)| Key | Meaning |
|---|---|
markdown | Extracted 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 |
title | Page title |
url | The URL you asked for |
final_url | The URL after redirects, re-checked by the SSRF guard. If unusable, the requested URL is reported with a final_url_suppressed threat |
fetched_at | UTC ISO-8601 timestamp |
status | ok, 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_status | The top-level HTTP status, or null |
truncated | Whether the token budget cut the content |
threats | What was stripped; empty when nothing was found |
matches | With 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_aside | With query: scoring passages the relevance floor dropped |
provenance | Content 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.
type | Carries |
|---|---|
hidden_css | The hiding reason, an 80-character excerpt and the DOM location |
hidden_attribute | The same, for text in an alt, aria-label, aria-description or title attribute |
hidden_template | The same, for text inside a |
hidden_pdf | The same, for text a PDF drew invisibly, with the page as its location |
zero_width / bidi / tag | A codepoint and count in reason, detected on the served text |
report_truncated | How many entries the cap dropped |
final_url_suppressed | The page's final URL was unusable and not returned |
detection_degraded | Detection ran in the page's own JavaScript world, which the page can tamper with |
strip_incomplete | The 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.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
Nur der Anfang wird gezeigt; den Rest findest du im Repo