Context7
Up-to-date docs for AI agents
Beschreibung vom Entwickler (englisches Original)
Self-hosted, Tavily-compatible web search, extract, crawl and map tools for AI agents.
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.
SEARXNG_URLDu 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": {
"siftdog": {
"command": "uvx",
"args": [
"siftdog",
"mcp"
],
"env": {
"SEARXNG_URL": "your-value"
}
}
}
}Führe das in deinem Terminal aus
claude mcp add siftdog --env SEARXNG_URL=your-value -- uvx siftdog mcpTrag die leeren Werte ein, bevor du ihn startest.
In .cursor/mcp.json in deinem Projekt oder in ~/.cursor/mcp.json einfügen
{
"mcpServers": {
"siftdog": {
"command": "uvx",
"args": [
"siftdog",
"mcp"
],
"env": {
"SEARXNG_URL": "your-value"
}
}
}
}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": {
"siftdog": {
"type": "stdio",
"command": "uvx",
"args": [
"siftdog",
"mcp"
],
"env": {
"SEARXNG_URL": "your-value"
}
}
}
}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.
SEARXNG_URL envDiese 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 6. Nov. 2026
Der Registry-Name wurde mit dem GitHub-Konto khsarvar 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 (0.3.0) kam vor 39 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.
[Website](https://siftdog.com/) · [Benchmark](https://siftdog.com/benchmark/) · [Blog](https://siftdog.com/blog/) · [Hosted waitlist](https://siftdog.com/hosted/)
Siftdog is an open-source, self-hosted web search API for AI agents and LLM apps, and a drop-in replacement for the [Tavily](https://tavily.com) API. It serves the same /search, /extract, /crawl and /map endpoints with the same request and response shapes, so code written for Tavily (including the official Python SDK and the LangChain integration) works against your own server by changing only the base URL. It needs no search API key.
advanced depth fetches each page and returns its most relevant chunksinclude_answer) written by Claude from the retrieved results/mcp or stdio with siftdog mcpPoint the official Tavily clients at your Siftdog server with api_base_url. The key can be any string when auth is disabled, or one of your API_KEYS.
from tavily import TavilyClient
client = TavilyClient(api_key="your-siftdog-key", api_base_url="http://localhost:8000") results = client.search("latest python release", search_depth="advanced", max_results=5) pages = client.extract(urls=["https://en.wikipedia.org/wiki/Okapi_BM25"])
LangChain, through langchain-tavily:
from langchain_tavily import TavilySearch
search = TavilySearch( max_results=5, tavily_api_key="your-siftdog-key", api_base_url="http://localhost:8000" ) search.invoke({"query": "what is BM25 ranking"})
Tested with tavily-python 0.8.4 (search, extract, crawl, map; sync and async) and langchain-tavily 0.2.18 (search, extract).
The full stack, with a SearXNG instance for /search, using the published image:
git clone https://github.com/khsarvar/siftdog && cd siftdog
cp .env.example .env # optional: set API_KEYS and ANTHROPIC_API_KEY docker compose up
Try a search:
curl -s localhost:8000/search -H "Content-Type: application/json" \
-d '{"query": "latest python release", "search_depth": "advanced"}'
If you set API_KEYS, add -H "Authorization: Bearer ". OpenAPI docs are served at http://localhost:8000/docs.
docker run -p 8000:8000 ghcr.io/khsarvar/siftdog
/extract, /crawl and /map work on their own. For /search, point it at a SearXNG instance with the JSON format enabled: -e SEARXNG_URL=http://your-searxng:8080. Images are published for linux/amd64 and linux/arm64, tagged latest and by version (0.1.0, 0.1).
pip install siftdog
SEARXNG_URL=http://your-searxng:8080 siftdog --port 8000
Configuration is read from environment variables or a .env file (see Configuration).
Siftdog is also an MCP server with four read-only tools: siftdog_search, siftdog_extract, siftdog_crawl and siftdog_map.
Connect to a running Siftdog server (Streamable HTTP at /mcp). With Claude Code:
claude mcp add --transport http siftdog http://localhost:8000/mcp \
--header "Authorization: Bearer " # omit the header if API_KEYS is empty
Or run it locally over stdio with uv, no server needed. SEARXNG_URL is only needed for siftdog_search:
claude mcp add siftdog -e SEARXNG_URL=http://your-searxng:8080 -- uvx siftdog mcp
Claude Desktop (claude_desktop_config.json), Cursor (.cursor/mcp.json) and most other clients take the same command as JSON:
{
"mcpServers": { "siftdog": { "command": "uvx", "args": ["siftdog", "mcp"], "env": { "SEARXNG_URL": "http://your-searxng:8080" } } } }
API keys work as for the REST API: send Authorization: Bearer , or append ?api_key= to the URL for clients that can't set headers (URLs can end up in logs, so prefer the header). The HTTP endpoint only answers requests addressed to localhost unless you list your hostname in MCP_ALLOWED_HOSTS.
| Siftdog | Tavily | Firecrawl | crw | |
|---|---|---|---|---|
| License | MIT | Proprietary (hosted service) | AGPL-3.0 | AGPL-3.0 |
| Self-hosted | Yes | No | Yes | Yes (also a managed API) |
| Tavily-compatible API | Yes | — | No (own API) | No (own API) |
| Search source | SearXNG metasearch | Proprietary | — | SearXNG (bundled) |
| JavaScript rendering | No (static HTML) | — | Yes | Yes (Lightpanda, Chrome fallback) |
| MCP server | Yes (HTTP and stdio) | Yes | Yes | Yes |
| Language | Python | — | TypeScript | Rust |
Measured results: Siftdog vs Tavily search benchmark (reproducible with bench/).
When to pick something else: if you'd rather not run infrastructure, or you want Tavily's neural reranking, use hosted Tavily. If you need JavaScript-rendered pages or a scraping platform with more features, look at Firecrawl or crw. Siftdog is for teams that want the Tavily API on their own servers under a permissive license.
Siftdog is an open-source web search and extraction API for AI agents. It reproduces the Tavily API (/search, /extract, /crawl, /map) on infrastructure you run yourself, using SearXNG for search results, trafilatura for content extraction and BM25 for relevance ranking.
For the four core endpoints, yes. The request and response fields match Tavily's, and the official tavily-python SDK and langchain-tavily work by setting api_base_url. The differences: relevance scores come from BM25 rather than a neural reranker, instructions (crawl/map) and include_image_descriptions (search) are accepted but ignored, and Tavily's /research endpoint isn't implemented.
No. Search results come from SearXNG, which queries public search engines. The only optional key is ANTHROPIC_API_KEY, used when a request sets include_answer.
Yes, through the official langchain-tavily package. Pass api_base_url pointing at your Siftdog server, as in the example above.
Yes. The API server exposes MCP over Streamable HTTP at /mcp, and uvx siftdog mcp runs it over stdio for local clients such as Claude Desktop and Cursor. See Use with MCP clients.
/search return 502 "failing engines"?SearXNG gets its results by querying public search engines (Brave, DuckDuckGo, Google and others), and those engines rate-limit or CAPTCHA an IP that sends many searches. When every engine is failing, Siftdog returns 502 with the engines and reasons, for example failing engines: brave (Suspended: too many requests), duckduckgo (CAPTCHA), rather than an empty result list your agent would mistake for "nothing found". Engines recover on their own, from minutes to about a day. If some engines still work, you get their results and the server logs which engines were down. To reduce blocking, enable more engines in docker/searxng/settings.yml and avoid bursts of identical searches.
Set API_KEYS so only your clients can call it. /extract and /crawl fetch caller-supplied URLs, so Siftdog refuses private, loopback and link-local addresses, checked on every redirect and at connect time against the exact address used, which also stops DNS rebinding.
Yes: pip install siftdog, then run siftdog with SEARXNG_URL pointing at any SearXNG instance with the JSON output format enabled. /extract, /crawl and /map work without SearXNG.
python3 -m venv .venv && .venv/bin/pip install -e ".[dev]"
docker compose up searxng -d # uncomment its ports: in docker-compose.yml first .venv/bin/siftdog # http://127.0.0.1:8000, docs at /docs .venv/bin/pytest # offline test suite .venv/bin/ruff check . && .venv/bin/ruff format .
All endpoints take JSON POST bodies and a Authorization: Bearer header (a legacy api_key body field is also accepted). If API_KEYS is empty, auth is disabled.
| Endpoint | Purpose | Key parameters |
|---|---|---|
/search | Web search | query, search_depth (basic/advanced), topic (general/news), time_range, max_results, chunks_per_source, include_answer, include_raw_content, include_images, include_domains, exclude_domains |
/extract | Clean content from up to 20 URLs | urls, extract_depth, format (markdown/text), include_images |
/crawl | Crawl a site and return page content | url, max_depth, max_breadth, limit, select_paths, exclude_paths, select_domains, exclude_domains, allow_external, format |
/map | List a site's URLs without content | same traversal parameters as /crawl |
Differences from hosted Tavily: instructions (crawl/map) and include_image_descriptions are accepted but ignored; relevance scores come from BM25, not a neural reranker.
Environment variables (see .env.example): API_KEYS, SEARXNG_URL, ANSWER_ENABLED, ANSWER_MODEL, ANSWER_EFFORT, FETCH_TIMEOUT, FETCH_CONCURRENCY, FETCH_MAX_BYTES, ALLOW_PRIVATE_NETWORKS, CRAWL_MAX_LIMIT, MCP_ALLOWED_HOSTS.
MCP_ALLOWED_HOSTS lists the hostnames the /mcp endpoint answers besides localhost, for example search.example.com,search.example.com:*. Requests addressed to any other host get 421, which protects a local server from DNS-rebinding attacks by web pages.
Security: /extract and /crawl make the server fetch caller-supplied URLs. Requests to private, loopback and link-local addresses are blocked (including via redirects) unless ALLOW_PRIVATE_NETWORKS=true. The check runs at connect time against the exact address being connected to, so DNS rebinding can't get around it. Fetches of user URLs ignore HTTP(S)_PROXY, since a proxy would hide the destination address. As defense in depth for hostile multi-tenant deployments, also restrict egress at the network level.
Siftdog is released under the MIT License. The "Siftdog" name is covered separately by the trademark policy: use the code freely, but forks and hosted services need a different name.