langchain-tavily
An integration package connecting Tavily and LangChain
Decision gist · record as of 2026-08-14
Yes. The package is actively maintained, has low install friction, carries a permissive MIT license, and integrates cleanly into LangChain workflows. It fills a genuine need for agents that require web search and content extraction. The main gotcha is the requirement for a Tavily API key and account setup, but that is external to the package itself.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires a Tavily API key obtained by creating an account at https://app.tavily.com/sign-in and setting the TAVILY_API_KEY environment variable.
- Low friction install with four runtime dependencies (langchain-core, langchain, aiohttp, requests).
- Active maintenance with recent commits; last release was 120 days ago and the repository is not archived.
License · maintenance · safety
MIT (permissive) — MIT license permits commercial and private use with minimal restrictions—include a copy of the license and copyright notice in distributions.
last release 2026-04-16 (120 days) · last repo commit 2026-08-07 · 25 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 793,778 downloads/mo, #5,040 on PyPI
Alternatives
Verify before relying
pip install langchain-tavily
import os
from langchain_tavily import TavilySearch
os.environ["TAVILY_API_KEY"] = "your-api-key"
tool = TavilySearch(max_results=5, topic="general")
result = tool.invoke({"query": "What happened at the last wimbledon"})- Whether Tavily API key provisioning or rate limits impose practical constraints on typical usage patterns.
- Performance characteristics of search depth options ('basic', 'advanced', 'fast', 'ultra-fast') and their impact on latency.
- Whether the package handles concurrent requests reliably given its aiohttp dependency.
What it is and what it does
langchain-tavily is a LangChain integration that wraps Tavily's web search and content extraction APIs. It provides two main tools: TavilySearch for querying the web with customizable parameters (search depth, time range, domain filtering, result format), and TavilyExtract for extracting structured content from URLs. Both tools are designed to work seamlessly with LangChain agents, allowing language models to dynamically invoke web searches and extract page data as part of agentic workflows.
The package depends on langchain-core, langchain, aiohttp, and requests. It requires a Tavily API key (obtained by creating an account at tavily.com) and supports Python 3.10 through 3.13. The tools accept numerous optional parameters at instantiation (max_results, topic, include_answer, search_depth, time_range, domain filters) and some parameters can be overridden at invocation time, though response-size parameters like include_answer and include_raw_content are fixed at instantiation to prevent context window issues.
Use it for
- Build an AI research assistant that searches the web for current information and synthesizes answers to user queries.
- Create an agent that filters search results by domain, date range, or geography to find domain-specific or time-sensitive information.
- Extract and parse content from multiple URLs in bulk to feed structured data into downstream LLM processing.
- Augment a chatbot with real-time web search capability so it can answer questions about recent events or breaking news.
- Implement a fact-checking workflow where an agent searches for corroborating sources and extracts their content.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes.
The package is actively maintained, has low install friction, carries a permissive MIT license, and integrates cleanly into LangChain workflows. It fills a genuine need for agents that require web search and content extraction. The main gotcha is the requirement for a Tavily API key and account setup, but that is external to the package itself.
Install
langchain-tavily on PyPI
Before you install
Low friction install with four runtime dependencies (langchain-core, langchain, aiohttp, requests). Active maintenance with recent commits; last release was 120 days ago and the repository is not archived.
Requires a Tavily API key obtained by creating an account at https://app.tavily.com/sign-in and setting the TAVILY_API_KEY environment variable.
License in practice
MIT license permits commercial and private use with minimal restrictions—include a copy of the license and copyright notice in distributions.
Quickstart
pip install langchain-tavily
import os
from langchain_tavily import TavilySearch
os.environ["TAVILY_API_KEY"] = "your-api-key"
tool = TavilySearch(max_results=5, topic="general")
result = tool.invoke({"query": "What happened at the last wimbledon"})Verify before relying
- Whether Tavily API key provisioning or rate limits impose practical constraints on typical usage patterns.
- Performance characteristics of search depth options ('basic', 'advanced', 'fast', 'ultra-fast') and their impact on latency.
- Whether the package handles concurrent requests reliably given its aiohttp dependency.
Package facts
| License | MIT permissive |
| Python support | Supports the current Python release <4.0,>=3.10 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 4 packageslangchain-corelangchainaiohttprequests |
| Maintenance | Actively maintained 120 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 793,778 / month, #5,040 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | License :: OSI Approved :: MIT LicenseProgramming Language :: Python :: 3Programming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13 |
Evidence: langchain_tavily-0.2.18-py3-none-any.whl
Tags
Let your AI agent find packages like this
Example. Real query, live index.
You found this page by searching. An agent finds it by wishing: SkillFed indexes 14,416 PyPI packages by what they can do, searchable in plain language.
wish › “tavily search api wrapper”
- langchain-tavilyIntegrates Tavily's web search and content extraction APIs into…
- tavily-pythonPython SDK for the Tavily API, providing web search, content…
- tavily-cliTavily CLI provides command-line and programmatic access to Tavily's…
Give your agent the search over MCP, or paste the wish link into any chat.
More Artificial Intelligence packages
LiteLLM provides a unified Python interface to call 100+ LLM providers (OpenAI, Anthropic, Gemini, Bedrock, Azure, and others) using OpenAI-compatible API format, available as both a Python SDK and a self-hosted AI Gateway proxy server.
Install it if you need to work with multiple LLM providers or want to centralize LLM routing in your organization.
Client library and CLI tool for downloading, uploading, and managing models, datasets, and repositories on the Hugging Face Hub platform.
Install it if you work with Hugging Face Hub models or datasets.
LangChain provides a framework for building agents and LLM-powered applications by composing language models, tools, and memory through a unified API that abstracts over multiple model providers.
hf-xet provides chunk-based deduplication and efficient file transfer for the Hugging Face Hub, enabling faster uploads and downloads of large files with local disk caching.
Tokenizers converts raw text into token sequences for NLP models, with support for training custom vocabularies and using pre-built tokenizers (BPE, WordPiece) optimized for speed via Rust.
Transformers provides a unified framework for loading, fine-tuning, and running state-of-the-art pretrained models across text, vision, audio, video, and multimodal tasks using PyTorch, JAX, or TensorFlow.
Install it if you need to run or train any transformer-based model for NLP, vision, audio, or multimodal tasks.
See also tavily-python · tavily-cli · langchain-azure-ai · zenpyre · langchain-cli · langchain-cohere · langchain-openai · composio-langchain · Crawl4AI