# Exa — AI-Native Search API for Agent Pipelines

> Search engine built for AI agents with semantic understanding. Exa returns clean content (not links) using neural search, ideal for RAG pipelines and research automation.

## Install

Save as a script file and run:

## Quick Use

```bash
pip install exa-py
```

```python
from exa_py import Exa

exa = Exa(api_key="...")

# Semantic search — understands meaning, not just keywords
results = exa.search_and_contents(
    "best practices for building RAG pipelines",
    num_results=5,
    text=True,
)

for r in results.results:
    print(f"Title: {r.title}")
    print(f"Content: {r.text[:200]}")
    print("---")
```

## What is Exa?

Exa is a search engine built specifically for AI applications. Unlike Google (designed for humans clicking links), Exa uses neural search to understand query meaning and returns clean, structured content — full text, not just URLs. This makes it ideal for RAG pipelines, research agents, and any AI workflow that needs high-quality web knowledge.

**Answer-Ready**: Exa is an AI-native search API using neural search. Returns clean content (not links) with semantic understanding. Built for RAG pipelines and AI agents. Supports search, similarity finding, and content extraction. MCP server available. Used by leading AI companies.

**Best for**: AI agents needing web search with clean content extraction. **Works with**: Any LLM framework, LangChain, LlamaIndex, Claude Code via MCP. **Setup time**: Under 2 minutes.

## Core Features

### 1. Semantic Search

```python
# Understands meaning, not just keyword matching
results = exa.search(
    "papers about attention mechanisms in transformers",
    num_results=10,
    type="neural",  # or "keyword" for traditional search
)
```

### 2. Search + Contents (One Call)

```python
# Get search results with full text content
results = exa.search_and_contents(
    "Claude Code tips and tricks",
    num_results=5,
    text={"max_characters": 3000},  # Full text extraction
    highlights=True,                 # Key excerpts
)
```

### 3. Find Similar

```python
# Find pages similar to a given URL
results = exa.find_similar_and_contents(
    "https://docs.anthropic.com/en/docs/claude-code",
    num_results=5,
    text=True,
)
```

### 4. Content Extraction Only

```python
# Extract content from known URLs
contents = exa.get_contents(
    ["https://example.com/article1", "https://example.com/article2"],
    text=True,
)
```

### 5. Filtering

```python
results = exa.search(
    "AI coding tools",
    num_results=10,
    start_published_date="2026-01-01",
    include_domains=["github.com", "arxiv.org"],
    exclude_domains=["reddit.com"],
    category="research paper",
)
```

## Exa vs Google/Tavily/Brave

| Feature | Exa | Google | Tavily | Brave |
|---------|-----|--------|--------|-------|
| Neural search | Yes | No | Partial | No |
| Returns content | Yes | Links only | Yes | Snippets |
| Find similar | Yes | No | No | No |
| AI-optimized | Yes | No | Yes | Partial |
| MCP server | Yes | No | Yes | Yes |
| Pricing | Per search | Per search | Per search | Per search |

## MCP Integration

```json
{
  "mcpServers": {
    "exa": {
      "command": "npx",
      "args": ["-y", "exa-mcp-server"],
      "env": { "EXA_API_KEY": "..." }
    }
  }
}
```

## FAQ

**Q: How is it different from Tavily?**
A: Exa uses proprietary neural search (trained embeddings), while Tavily wraps traditional search with AI extraction. Exa's "find similar" feature is unique.

**Q: How much does it cost?**
A: Free tier available with limited searches. Paid plans from $5/month.

**Q: Can Claude Code use it?**
A: Yes, via the Exa MCP server or direct API calls in scripts.

## Source & Thanks

> Created by [Exa](https://exa.ai).
>
> [exa.ai](https://exa.ai) — AI-native search engine

<!-- ZH -->

## 快速使用

```bash
pip install exa-py
```

一行代码进行 AI 语义搜索，返回干净内容而非链接。

## 什么是 Exa？

为 AI 应用设计的搜索引擎，神经搜索理解查询语义，返回干净的全文内容。RAG 管线和研究 Agent 的理想选择。

**一句话总结**：AI 原生搜索 API，神经搜索返回干净内容（非链接），语义理解 + 相似发现 + 内容提取，MCP 服务器可用，RAG 管线首选。

**适合人群**：需要高质量 Web 搜索的 AI Agent 和 RAG 管线。

## 核心功能

### 1. 语义搜索 — 理解含义而非关键词匹配
### 2. 搜索+内容 — 一次调用返回全文
### 3. 相似发现 — 找到与指定 URL 相似的页面
### 4. MCP 集成 — Claude Code/Cursor 直接使用

## 常见问题

**Q: 和 Tavily 区别？**
A: Exa 用自研神经搜索，Tavily 包装传统搜索。Exa 独有"相似发现"功能。

## 来源与致谢

> [exa.ai](https://exa.ai) — AI 原生搜索引擎

---
Source: https://tokrepo.com/en/workflows/f550d644-23a1-42f9-a696-dda0b398e4dc
Author: Script Depot