Context7
Up-to-date docs for AI agents
作者による説明(英語の原文)
Self-hosted, Tavily-compatible web search, extract, crawl and map tools for AI agents.
この3つを1つのスコアにまとめることはしません。意見、測定、人気はそれぞれ別のものだからです。
このサーバーのやさしい解説はまだ書いていません。以下はレジストリから読み取った事実です。
使っているAIアプリを選んで、設定をコピーしてください。
SEARXNG_URL必要なもの
どのアプリを使っていますか?
上でアプリを選んでください。選んだアプリを覚えておくので、次からはボタンに「…にインストール」と表示されます。
Claude Desktop → Settings → Developer → Edit Config を開き、claude_desktop_config.json にこれを貼り付けます
{
"mcpServers": {
"siftdog": {
"command": "uvx",
"args": [
"siftdog",
"mcp"
],
"env": {
"SEARXNG_URL": "your-value"
}
}
}
}ターミナルでこれを実行します
claude mcp add siftdog --env SEARXNG_URL=your-value -- uvx siftdog mcp動かす前に、空欄の値を入力してください。
プロジェクトの .cursor/mcp.json、または ~/.cursor/mcp.json に貼り付けます
{
"mcpServers": {
"siftdog": {
"command": "uvx",
"args": [
"siftdog",
"mcp"
],
"env": {
"SEARXNG_URL": "your-value"
}
}
}
}ブラウザがアプリを開いてよいか確認し、そのあとアプリが設定を表示して確認を求めます。キーの値は空欄のままなので、自分で入力してください。
プロジェクトの .vscode/mcp.json に貼り付けます
{
"servers": {
"siftdog": {
"type": "stdio",
"command": "uvx",
"args": [
"siftdog",
"mcp"
],
"env": {
"SEARXNG_URL": "your-value"
}
}
}
}ブラウザがアプリを開いてよいか確認し、そのあとアプリが設定を表示して確認を求めます。キーの値は空欄のままなので、自分で入力してください。
これはパソコンで動くサーバーですが、ChatGPTがつなげるのはインターネット上のサーバーだけです。ほかのアプリを選んでください。
選んだアプリは、この端末のCookieに保存されます。アカウントは不要です。
SEARXNG_URL envこの設定は、作者のレジストリ登録情報から作成しています。READMEと違う場合は、READMEに従ってください。
パソコンで動くサーバーです。インストールすると、ツール一覧がAIアプリに表示されます。
誰でも見られる情報をチェックしており、コードは読んでいません。当てはまらない項目は数に入れていません。 · 2026年11月6日にチェック
レジストリ名は、リポジトリを所有するGitHubアカウント khsarvar で確認済みです
このリポジトリはまだGitHubから読み取っていません
このリポジトリはまだGitHubから読み取っていません
これはパソコンで動くため、インターネット上のエンドポイントはありません
パソコンで動き、代わりにローカルの設定を使います
パソコンで動くサーバーです。ツール一覧を読み取れるのは、インターネット上のエンドポイントがある場合だけです
レジストリでこのカテゴリにある有効なすべてのサーバーと比較しています。スターは、公開者がリポジトリの所有者である場合だけ数えます。
当てはまる基本チェック1項目のうち1項目に合格しました。コードは読んでいません。キーやトークンを追加する前に、サーバーがどんなアクセスを求めているかを確認し、必要な権限だけを持つキーを使ってください。
レジストリには必須のキーは載っていません。ただし、最初に使うときにサインインを求めるサーバーもあります。
あなたのパソコンで動きます。必要なときにAIアプリが起動し、データは作者のサーバーを通りません(サーバー自体がオンラインサービスを呼び出す場合を除きます)。
GitHubリポジトリの最終更新は–、最新バージョン(0.3.0)がレジストリに届いたのは39 日前です。
Claude Desktop、Claude Code、Cursor、VS CodeなどのMCP対応アプリで使えます。パソコンにPython (uv)も必要です。
同じカテゴリには:Context7, Codebase Memory, Exa
同じカテゴリで、ほかの作者が作ったサーバー。スターの多い順。
カードの見方:★ GitHubスターi3つの柱:レビュー · チェック · 利用状況i更新=最新バージョンをレジストリに公開した日i
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.
作者のリポジトリから書かれたとおりにコピーしたものです。PopNx MCPは内容を確認・推奨していません。HTML、画像、スクリプトは取り除いています。リンクはこのサイトの外へ移動します。
[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.