# Exa Search > Search the web using Exa's AI-powered search API. Supports semantic search, content extraction, direct answers, and deep research with structured output. - Skill: `nicolaischmid/exa-search` (Agent Skill, multi-file: 2 files) - Install (CLI): `npx skillmds@latest add nicolaischmid/exa-search` - Raw SKILL.md: https://api.skillmd.com/api/skills/nicolaischmid/exa-search/raw - Safety review: pending - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: Research & Search - License: MIT - Author: nicolaischmid (https://skillmd.com/u/nicolaischmid) - Updated: 2026-09-17 - Page: https://skillmd.com/skills/nicolaischmid/exa-search --- # Exa Web Search Search the web using Exa's AI-powered search API. Exa provides semantic search capabilities optimized for AI applications. ## Configuration Config file: `~/.config/exa-search/config.json` ```json { "api_key": "your-exa-api-key-here" } ``` ### Getting an API key 1. Go to https://dashboard.exa.ai/api-keys 2. Sign up or log in to your Exa account 3. Create a new API key ### Troubleshooting config If requests fail, verify the config: ```bash # Check config exists and is valid JSON cat ~/.config/exa-search/config.json | jq . # Test connection curl -s -X POST "https://api.exa.ai/search" \ -H "x-api-key: $(jq -r .api_key ~/.config/exa-search/config.json)" \ -H "Content-Type: application/json" \ -d '{"query": "test", "numResults": 1}' | jq '.results | length' ``` **Common issues:** - `401 Unauthorized`: API key is invalid → get a new key from dashboard - `Connection refused`: Network issue or API is down - `null` or parse error: Config file is missing or malformed If config is broken, guide the user to provide their Exa API key, then create/update the config: ```bash mkdir -p ~/.config/exa-search cat > ~/.config/exa-search/config.json << 'EOF' { "api_key": "USER_PROVIDED_API_KEY" } EOF ``` ## Endpoint Selection Guide Choose the appropriate endpoint based on user intent: | Endpoint | Use When | |----------|----------| | `/search` | Need to find web pages, research topics, or get content from multiple sources | | `/contents` | Have specific URLs and need to extract their full content | | `/answer` | Need a direct, concise answer to a factual question | | `/research/v1` | Need in-depth research with structured output, multi-step analysis, or comprehensive reports | ## API Examples ### Load API key ```bash EXA_API_KEY=$(jq -r .api_key ~/.config/exa-search/config.json) ``` ### 1. Search (`/search`) Semantic search with optional content extraction. Returns results with their contents. ```bash # Basic search curl -s -X POST "https://api.exa.ai/search" \ -H "x-api-key: $EXA_API_KEY" \ -H "Content-Type: application/json" \ -d '{ "query": "latest developments in AI agents", "numResults": 10 }' | jq '.results[] | {title, url, publishedDate}' # Search with content extraction curl -s -X POST "https://api.exa.ai/search" \ -H "x-api-key: $EXA_API_KEY" \ -H "Content-Type: application/json" \ -d '{ "query": "best practices for RAG systems", "numResults": 5, "contents": { "text": true, "highlights": { "numSentences": 3, "highlightsPerUrl": 2 }, "summary": {} } }' | jq '.results[] | {title, url, summary, highlights}' # Search with date filters and domain restrictions curl -s -X POST "https://api.exa.ai/search" \ -H "x-api-key: $EXA_API_KEY" \ -H "Content-Type: application/json" \ -d '{ "query": "OpenAI announcements", "numResults": 10, "startPublishedDate": "2024-01-01T00:00:00.000Z", "includeDomains": ["openai.com", "techcrunch.com", "theverge.com"], "contents": { "text": {"maxCharacters": 1000}, "summary": {} } }' | jq # Search with category filter curl -s -X POST "https://api.exa.ai/search" \ -H "x-api-key: $EXA_API_KEY" \ -H "Content-Type: application/json" \ -d '{ "query": "transformer architecture papers", "numResults": 10, "category": "research paper", "contents": { "text": true, "summary": {} } }' | jq # Deep search for comprehensive results curl -s -X POST "https://api.exa.ai/search" \ -H "x-api-key: $EXA_API_KEY" \ -H "Content-Type: application/json" \ -d '{ "query": "climate change mitigation strategies", "type": "deep", "numResults": 20, "contents": { "text": true, "summary": {} } }' | jq ``` **Search types:** - `auto` (default): Intelligently combines neural and other methods - `neural`: Pure semantic/embeddings-based search - `fast`: Quick keyword-based search - `deep`: Comprehensive search with query expansion **Categories:** `company`, `research paper`, `news`, `pdf`, `github`, `tweet`, `personal site`, `financial report`, `people` ### 2. Contents (`/contents`) Extract content from specific URLs. ```bash # Get content from URLs curl -s -X POST "https://api.exa.ai/contents" \ -H "x-api-key: $EXA_API_KEY" \ -H "Content-Type: application/json" \ -d '{ "urls": [ "https://arxiv.org/abs/2307.06435", "https://example.com/article" ], "text": true, "summary": {}, "highlights": { "numSentences": 2, "highlightsPerUrl": 3 } }' | jq '.results[] | {url, title, summary, highlights}' # Get content with livecrawl for fresh data curl -s -X POST "https://api.exa.ai/contents" \ -H "x-api-key: $EXA_API_KEY" \ -H "Content-Type: application/json" \ -d '{ "urls": ["https://example.com/news"], "text": {"maxCharacters": 5000}, "livecrawl": "preferred" }' | jq ``` **Livecrawl options:** - `never`: Only use cache - `fallback`: Livecrawl when cache is empty (default) - `preferred`: Try livecrawl first, fall back to cache - `always`: Always livecrawl, never use cache ### 3. Answer (`/answer`) Get direct answers to questions, grounded in web search results. ```bash # Get a direct answer curl -s -X POST "https://api.exa.ai/answer" \ -H "x-api-key: $EXA_API_KEY" \ -H "Content-Type: application/json" \ -d '{ "query": "What is the current population of Tokyo?" }' | jq '{answer, citations: [.citations[] | {title, url}]}' # Answer with full source text curl -s -X POST "https://api.exa.ai/answer" \ -H "x-api-key: $EXA_API_KEY" \ -H "Content-Type: application/json" \ -d '{ "query": "What are the main features of GPT-4?", "text": true }' | jq ``` ### 4. Research (`/research/v1`) Long-running research tasks with structured output. This is asynchronous - you create a task and poll for results. ```bash # Create a research task with structured output RESEARCH_RESPONSE=$(curl -s -X POST "https://api.exa.ai/research/v1" \ -H "x-api-key: $EXA_API_KEY" \ -H "Content-Type: application/json" \ -d '{ "model": "exa-research", "instructions": "Compare the top 3 cloud providers (AWS, Azure, GCP) on pricing for compute instances. Return structured data.", "outputSchema": { "type": "object", "required": ["providers"], "properties": { "providers": { "type": "array", "items": { "type": "object", "required": ["name", "computePricing", "strengths"], "properties": { "name": {"type": "string"}, "computePricing": {"type": "string"}, "strengths": {"type": "array", "items": {"type": "string"}} } } } } } }') RESEARCH_ID=$(echo "$RESEARCH_RESPONSE" | jq -r '.researchId') echo "Research ID: $RESEARCH_ID" # Poll for results (repeat until status is "completed" or "failed") curl -s "https://api.exa.ai/research/v1/$RESEARCH_ID" \ -H "x-api-key: $EXA_API_KEY" | jq '{status, output}' # Simple research without schema (returns markdown report) curl -s -X POST "https://api.exa.ai/research/v1" \ -H "x-api-key: $EXA_API_KEY" \ -H "Content-Type: application/json" \ -d '{ "model": "exa-research", "instructions": "Summarize the latest developments in quantum computing from the past 6 months." }' | jq ``` **Research models:** - `exa-research` (default): Balanced speed and quality, adapts to task difficulty - `exa-research-pro`: Maximum quality, more thorough analysis (slower) **Best practices for research:** - Be explicit about what information you want - Describe how the agent should find information - Specify the desired output format - Keep schemas small (1-5 root fields) - Use enums in schemas for better accuracy ## API Reference ### Search Parameters | Parameter | Type | Description | |-----------|------|-------------| | `query` | string | The search query (required) | | `numResults` | integer | Number of results (max 100, default 10) | | `type` | string | Search type: `auto`, `neural`, `fast`, `deep` | | `category` | string | Filter by content type | | `includeDomains` | array | Only include results from these domains | | `excludeDomains` | array | Exclude results from these domains | | `startPublishedDate` | string | Only results published after (ISO 8601) | | `endPublishedDate` | string | Only results published before (ISO 8601) | | `includeText` | array | Must contain this text (max 1 string, 5 words) | | `excludeText` | array | Must not contain this text | | `contents` | object | Content extraction options | ### Contents Options | Parameter | Type | Description | |-----------|------|-------------| | `text` | boolean/object | Extract full page text | | `highlights` | object | Extract relevant snippets | | `summary` | object | Generate page summary | | `livecrawl` | string | Crawl freshness: `never`, `fallback`, `preferred`, `always` | ### Response Fields | Field | Description | |-------|-------------| | `requestId` | Unique request identifier | | `results` | Array of search results | | `results[].id` | Document ID (use with /contents) | | `results[].url` | Page URL | | `results[].title` | Page title | | `results[].publishedDate` | Publication date | | `results[].author` | Author if available | | `results[].text` | Full page content (if requested) | | `results[].highlights` | Relevant snippets (if requested) | | `results[].summary` | Page summary (if requested) | | `costDollars` | Request cost breakdown | ## Pricing Notes - **Search:** $0.005 per request (1-25 results), $0.025 (26-100 results) - **Deep Search:** $0.015 per request (1-25 results), $0.075 (26-100 results) - **Contents:** $0.001 per page for text/highlights/summary - **Answer:** Variable based on search and LLM usage - **Research:** Variable usage-based (searches + pages read + reasoning tokens)