exa-search-cli 0.1.5

AI-agent friendly CLI for Exa — neural web search, URL crawling, and deep research from the terminal.

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exa-search-cli

CLI for Exa — neural web search, URL crawling, and AI deep research from the terminal.

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What it does

exa-search-cli wraps the Exa API in four terminal commands. Exa is a search API built for AI applications — it searches by meaning, not keywords, which means it finds relevant pages even when the exact words are not present in the content.

exa-search searches the web. exa-crawl extracts clean readable text from any URL without HTML. exa-research submits a deep research task where Exa AI reads the web and synthesizes a structured answer; exa-research-status checks on that task and returns the result once it's ready.

Every command outputs clean --json for use in scripts, pipelines, and AI agent workflows.

Who it is for

• Developers who want web search access from shell scripts and automation pipelines
• AI agent developers who need structured, parseable web search output
• Researchers collecting, filtering, and crawling web content programmatically
• Anyone using Claude Code, Codex, Cursor, or Windsurf who wants to give their agent web access

Features

• Neural (semantic) search — finds pages by meaning, not keyword matching
• Find pages similar to any URL
• Filter by content type: news, tweet, github, research paper, pdf, and more
• Filter by date range and domain
• Full page text extraction from any URL (no HTML)
• AI deep research tasks with synthesized answers
• Clean --json output for every command

Installation

uv tool install exa-search-cli

No uv? Run curl -LsSf https://astral.sh/uv/install.sh | sh, or use pip install exa-search-cli.

Quick start

Get your API key at exa.ai (free tier available):

export EXA_API_KEY=your-key-here
exa-search "how do transformers work" --category "research paper"

Usage

# Neural search
exa-search "vision language models 2025" -n 10

# Find similar pages to a URL
exa-search --similar https://github.com/astral-sh/uv

# Filter by content type and date
exa-search "AI papers" --category "research paper" --start-date 2025-01-01

# Only specific domains
exa-search "documentation" --include-domain docs.python.org,docs.rs

# Exclude noisy domains
exa-search "tutorial" --exclude-domain medium.com,dev.to

# Crawl a page, get clean text
exa-crawl https://example.com -c 8000

# Deep research task
exa-research "current state of quantum error correction"
exa-research-status <research-id>   # check progress / fetch the result

# JSON output for pipelines
exa-search "topic" --json | jq -r '.results[].url'

All flags — exa-search:

Flag	Default	Description
-n / --num-results	8	Number of results
-t / --type	auto	auto · keyword · neural
--text	off	Fetch and show full page text
--category	—	news · tweet · github · research paper · pdf · company · personal site · linkedin profile · financial report
--start-date	—	Published on or after YYYY-MM-DD
--end-date	—	Published on or before YYYY-MM-DD
--include-domain	—	Comma-separated domains to include only
--exclude-domain	—	Comma-separated domains to exclude
--similar	—	Find pages similar to this URL
--json	off	Raw JSON output

All flags — exa-crawl: -c / --max-chars (default 5000), --json

All flags — exa-research: -m / --model (exa-research-fast · exa-research · exa-research-pro), --json

All flags — exa-research-status: --json

AI agent usage

exa-search-cli is stateless, read-only, and exits cleanly — designed to be called by AI coding assistants.

# Search and extract URLs (most common agent pattern)
exa-search "topic" --json | jq -r '.results[].url'

# Search → crawl first result
exa-search "topic" --json \
  | jq -r '.results[0].url' \
  | xargs exa-crawl -c 6000

# Find similar pages to a reference URL
exa-search --similar https://example.com --json

# Deep research, get synthesized answer
exa-research "topic" --json
exa-research-status <research-id> --json

JSON schema for exa-search --json:

{
  "results": [
    {
      "title": "...",
      "url": "...",
      "published_date": "2025-01-15T00:00:00.000Z",
      "author": "...",
      "highlights": ["excerpt..."],
      "text": "full text if --text was passed"
    }
  ]
}

See AGENTS.md for full schemas, exit codes, and environment reference.

→ Full documentation

Project metadata

• Author: Nolan Vale
• Brand: Nolan Vale Tools
• Focus: search automation, CLI workflows, AI-agent tooling, developer productivity
• License: MIT

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Built by Nolan Vale
Part of Nolan Vale Tools — practical open-source utilities for search, automation, AI agents, and developer workflows.