Tavily - AI Web Research & Search API
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Tavily Brief overview
Tavily is a developer-focused web search and web-access API designed for AI agents and LLM applications that need reliable, real-time information from the public web. Instead of returning only a list of links, Tavily aims to deliver structured results that are easier for an LLM to consume in agent workflows, retrieval-augmented generation (RAG), and automated research tasks.
At a high level, Tavily helps you: (1) search the web with LLM-friendly outputs, (2) extract readable content from specific URLs, and (3) optionally crawl or map sites for broader discovery. It’s commonly used when you want your AI app to “look things up” on demand, reduce hallucinations by grounding outputs in current sources, and keep your pipeline simple with a single web-access layer.
Simple how-to-use
- Create an account and get an API key from Tavily’s dashboard.
- Choose an integration method:
- Direct API calls (REST): Send a request to Tavily endpoints using your API key (useful for any language or serverless setup).
- Python SDK: Install the package, initialize the client with your API key, then call search/extract/crawl/map.
- JavaScript/TypeScript SDK: Install the npm package, initialize the client, then call the same core methods.
- Agent frameworks: Connect Tavily through supported ecosystem integrations (example: LangChain tools).
- Start with a simple web search (basic query) to return results in JSON.
- Optionally extract full content from a URL you found via search (useful for summarization, citation building, or RAG ingestion).
- Tune results as needed by adjusting parameters such as depth, result count, and whether to include an answer or raw content.
Tavily Key features and functions
- LLM-optimized web search: Returns structured, relevance-ranked results designed to be fed into LLM prompts or RAG pipelines.
- Source aggregation per request: Can aggregate results from multiple sites in a single call (commonly “up to 20” sources depending on configuration).
- Search depth controls: Choose lighter/faster “basic” searches or deeper “advanced” searches (which generally use more credits).
- Automatic parameter handling: Optional auto-configuration that can adjust search behavior based on query intent (while still allowing manual overrides).
- Content extraction: Pulls clean text/content from one or more URLs so you can summarize, quote, or embed into a knowledge base.
- Crawl and map capabilities: Helpful for scanning a domain, discovering pages, and building structured collections for downstream processing.
- Multiple developer entry points: Official Python and JavaScript/TypeScript SDKs, plus compatibility with agent tooling (and MCP support for certain clients).
Pricing
Tavily uses a credit-based pricing model. Your cost depends on your plan and how many credits an endpoint consumes (for example, advanced search depth can cost more than basic).
Common plan options include:
- Researcher: Free — 1,000 credits/month
- Pay-as-you-go:$0.008 per credit
- Project:$30/month — 4,000 credits/month
- Bootstrap:$100/month — 15,000 credits/month
- Startup:$220/month — 38,000 credits/month
- Growth:$500/month — 100,000 credits/month
- Enterprise: Custom pricing (typically for higher volume and tailored needs)
Notes: Credit usage varies by endpoint and settings (for instance, advanced search depth may consume 2 credits per request versus a lower-cost basic search). Always verify current credit costs in the official docs before estimating production spend.
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