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External jump (enhancement)
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Strengths
- Semantic search, understanding query intent rather than keyword matching
- Designed specifically for AI applications, returning structured data
- Supports obtaining the complete content of the web page (not just the summary)
- You can filter results by date, domain name, etc.
- Free credit is enough for testing and small projects
Best for
- Provide real-time network search capabilities for AI Agents
- Network data sources for building RAG systems
- Data acquisition for research tools
- Competitive product monitoring and industry information aggregation
- Literature discovery for academic research
API basic usage
Exa provides a simple Python SDK that can integrate semantic search with just a few lines of code.
Scenario
Basic semantic search
Prompt example
from exa_py import Exa
exa = Exa(api_key="your-exa-api-key")
# Semantic search (not keyword search)
results = exa.search(
"Latest breakthroughs in protein folding AI research",
num_results=5,
use_autoprompt=True # Automatically optimize queries
)
for result in results.results:
print(f"Title: {result.title}")
print(f"URL: {result.url}")
print(f"Published time: {result.published_date}")
print()Output / what to expect
Returns 5 semantically related web pages,
Better understanding of query intent than keyword search,
The results are of higher quality.
Tips
use_autoprompt=True lets Exa automatically optimize the query, usually giving better results.
Scenario
Get the complete content of the web page
Prompt example
from exa_py import Exa
exa = Exa(api_key="your-exa-api-key")
# Search and get complete content
results = exa.search_and_contents(
"AI regulation in Europe 2025",
num_results=3,
text=True, # Get the text of the article
highlights=True, # Get key fragments
start_published_date="2025-01-01" # Only content after 2025
)
for result in results.results:
print(f"Title: {result.title}")
print(f"Content summary: {result.text[:500]}...")
print()Output / what to expect
Get the full article content,
Can be used directly in RAG systems,
No additional web scraping steps required.
Tips
text=True will get the complete article content, which will consume more API quota and can be used on demand.