Exa Web Search & Content Extraction

Real-time web search and content extraction powered by Exa AI.

Prerequisite: Set EXA_API_KEY environment variable.

API Quick Reference

Endpoint	Purpose
POST /search	Web search with optional content retrieval
POST /contents	Extract content from specific URLs
POST /context	Find code examples and programming context

Usage

Web Search

# Basic search
curl -X POST 'https://api.exa.ai/search' \
  -H "x-api-key: $EXA_API_KEY" \
  -H 'Content-Type: application/json' \
  -d '{"query": "latest AI research", "text": true}'

# Deep search with more results
curl -X POST 'https://api.exa.ai/search' \
  -H "x-api-key: $EXA_API_KEY" \
  -H 'Content-Type: application/json' \
  -d '{"query": "React server components", "type": "deep", "numResults": 10, "text": true}'

# Fast search
curl -X POST 'https://api.exa.ai/search' \
  -H "x-api-key: $EXA_API_KEY" \
  -H 'Content-Type: application/json' \
  -d '{"query": "node.js version", "type": "fast"}'

Extract URL Content

curl -X POST 'https://api.exa.ai/contents' \
  -H "x-api-key: $EXA_API_KEY" \
  -H 'Content-Type: application/json' \
  -d '{"urls": ["https://docs.example.com/api"], "text": true}'

Code Context

curl -X POST 'https://api.exa.ai/context' \
  -H "x-api-key: $EXA_API_KEY" \
  -H 'Content-Type: application/json' \
  -d '{"query": "React useState hook examples", "tokensNum": 5000}'

Workflow

Think step-by-step when using Exa:

1. Choose the right endpoint based on the task:

   • Web research, searching topics → /search
   • Extracting content from specific URLs → /contents
   • Programming examples, code context → /context

2. Select search type for /search:

   • fast - Quick results, lower latency
   • auto - Balanced (default)
   • deep - Comprehensive, higher quality

3. Request content when needed using "text": true or "context": true

When to Use Each Endpoint

Use /search	Use /contents	Use /context
Finding relevant pages	You have a specific URL	Programming questions
General web research	Extracting known content	API/library usage
News and articles	Reading documentation	Code examples
Exploring options	Getting full article text	Implementation patterns

Search Types

Type	Use Case	Speed
fast	Quick lookups, simple queries	Fastest
auto	General purpose, balanced results	Medium
deep	Complex research, comprehensive coverage	Slowest

Rules

• Current year is 2026 - Use this for date-relative queries (e.g., "latest", "recent", "this year")
• Use "type": "fast" for simple factual queries
• Use "type": "deep" for research requiring comprehensive results
• Add "text": true to get full page content in search results
• Add "context": true for LLM-optimized context strings
• Use /context endpoint for programming questions instead of /search
• Prefer /contents when you have a specific URL to extract

References

• Search - Web search parameters and options
• Crawl - URL content extraction
• Code - Programming context search