The official LangChain integration for SERPdive, the AI Search API: your agent asks a question, the tool returns answer-ready web content that is extracted, cleaned, and sized for an LLM. On a public, replayable 1,000-question benchmark, SERPdive runs at the same speed as Tavily, feeds your LLM 20.2% fewer tokens, and wins 60.7% of decided quality duels.
There is a free tier, and it has no ceiling. The krill model is free and unlimited under fair use — no card, no credits, nothing to decrement. It returns the shortest set of sentences that still answers (about 700 tokens a search, roughly half what the usual alternatives send), one request at a time, at low priority. Use it to build; switch one word to mako when you need depth and steady latency.
pip install langchain-serpdiveGet a free API key (no card required) at serpdive.com/dashboard/keys and set it:
export SERPDIVE_API_KEY="sd_live_..."from langchain_serpdive import SerpdiveSearch
tool = SerpdiveSearch()
tool.invoke({"query": "latest developments in solid state batteries"})The output is a lean dict your model can quote and cite directly:
{
"query": "latest developments in solid state batteries",
"results": [
{
"url": "https://...",
"title": "...",
"date": "2026-07-11",
"content": "The fact-carrying text of the page, extracted and cleaned...",
},
...
],
}from langchain.chat_models import init_chat_model
from langgraph.prebuilt import create_react_agent
from langchain_serpdive import SerpdiveSearch
agent = create_react_agent(
init_chat_model("claude-sonnet-5"),
tools=[SerpdiveSearch()],
)
agent.invoke({"messages": [("user", "What changed in the EU AI Act this month?")]})SerpdiveSearch(
model="moby", # "mako" (default): key sentences, fast. "moby": full page text, deep research
answer=True, # also return a direct answer synthesized from the sources
max_results=5, # hard cap on delivered results, 1-10
api_key="sd_live_...", # defaults to SERPDIVE_API_KEY
)Localization is automatic: the language of the query picks where we search. There is no country parameter to configure. Failed searches are never billed.
- API reference
- Public benchmark (replayable end to end: same questions, same judge, your machine)
- Python SDK (this package is a thin layer over it)
- MCP server for Claude, Cursor and other MCP clients
MIT