Search and Retrieval APIs
Use Tavily with LangGraph
Tavily connects to LangGraph through a official adapter package path (langchain-tavily TavilySearch used as a LangChain tool in LangGraph agents). This page records what that connection looks like and links the evidence behind it.
Pairing facts
Why this pairing
A web access API built for AI agents: search, extract, map, crawl, and research endpoints behind one key.
Best for: Agents that need current web facts with cited results Research workflows that combine search with page extraction Teams that want one vendor for search and fetching
Not ideal for: Fully offline or self-hosted stacks High-volume crawling without a credit budget
Configuration
from langchain_tavily import TavilySearch
tools = [TavilySearch()]Source: https://docs.langchain.com/oss/python/integrations/providers/tavily. Examples use placeholders only.
Evidence
The Tavily provider page states langchain-tavily exposes Tavily endpoints as LangChain tools; LangGraph agents consume LangChain tools, and the LangGraph repository states LangChain provides integrations and composable components.
https://docs.langchain.com/oss/python/integrations/providers/tavily
Compatibility here means the cited page documents the pairing. It does not mean AgentsUse benchmarked the combination or that every version works unchanged. Pin versions, run the tool on a small job first, and review the first outputs before widening access.
Watch for
- Metered by credits, so unattended crawl loops need spending controls.
- A managed service: no self-hosted fallback when Tavily is down or a source blocks it.