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175 lines
4.9 KiB
Markdown
175 lines
4.9 KiB
Markdown
---
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name: exa-search
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description: Neural search via Exa MCP for web, code, and company research. Use when the user needs web search, code examples, company intel, people lookup, or AI-powered deep research with Exa's neural search engine.
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origin: ECC
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---
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# Exa Search
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Neural search for web content, code, companies, and people via the Exa MCP server.
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## When to Activate
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- User needs current web information or news
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- Searching for code examples, API docs, or technical references
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- Researching companies, competitors, or market players
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- Finding professional profiles or people in a domain
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- Running background research for any development task
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- User says "search for", "look up", "find", or "what's the latest on"
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## MCP Requirement
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Exa MCP server must be configured. Add to `~/.claude.json`:
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```json
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"exa-web-search": {
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"command": "npx",
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"args": [
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"-y",
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"exa-mcp-server",
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"tools=web_search_exa,web_search_advanced_exa,get_code_context_exa,crawling_exa,company_research_exa,linkedin_search_exa,deep_researcher_start,deep_researcher_check"
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],
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"env": { "EXA_API_KEY": "YOUR_EXA_API_KEY_HERE" }
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}
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```
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Get an API key at [exa.ai](https://exa.ai).
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## Core Tools
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### web_search_exa
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General web search for current information, news, or facts.
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```
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web_search_exa(query: "latest AI developments 2026", numResults: 5)
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```
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**Parameters:**
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| Param | Type | Default | Notes |
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|-------|------|---------|-------|
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| `query` | string | required | Search query |
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| `numResults` | number | 8 | Number of results |
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### web_search_advanced_exa
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Filtered search with domain and date constraints.
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```
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web_search_advanced_exa(
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query: "React Server Components best practices",
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numResults: 5,
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includeDomains: ["github.com", "react.dev"],
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startPublishedDate: "2025-01-01"
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)
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```
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**Parameters:**
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| Param | Type | Default | Notes |
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|-------|------|---------|-------|
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| `query` | string | required | Search query |
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| `numResults` | number | 8 | Number of results |
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| `includeDomains` | string[] | none | Limit to specific domains |
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| `excludeDomains` | string[] | none | Exclude specific domains |
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| `startPublishedDate` | string | none | ISO date filter (start) |
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| `endPublishedDate` | string | none | ISO date filter (end) |
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### get_code_context_exa
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Find code examples and documentation from GitHub, Stack Overflow, and docs sites.
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```
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get_code_context_exa(query: "Python asyncio patterns", tokensNum: 3000)
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```
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**Parameters:**
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| Param | Type | Default | Notes |
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|-------|------|---------|-------|
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| `query` | string | required | Code or API search query |
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| `tokensNum` | number | 5000 | Content tokens (1000-50000) |
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### company_research_exa
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Research companies for business intelligence and news.
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```
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company_research_exa(companyName: "Anthropic", numResults: 5)
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```
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**Parameters:**
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| Param | Type | Default | Notes |
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|-------|------|---------|-------|
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| `companyName` | string | required | Company name |
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| `numResults` | number | 5 | Number of results |
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### people_search_exa
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Find professional profiles and bios.
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```
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people_search_exa(query: "AI safety researchers at Anthropic", numResults: 5)
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```
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### crawling_exa
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Extract full page content from a URL.
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```
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crawling_exa(url: "https://example.com/article", tokensNum: 5000)
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```
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**Parameters:**
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| Param | Type | Default | Notes |
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|-------|------|---------|-------|
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| `url` | string | required | URL to extract |
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| `tokensNum` | number | 5000 | Content tokens |
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### deep_researcher_start / deep_researcher_check
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Start an AI research agent that runs asynchronously.
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```
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# Start research
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deep_researcher_start(query: "comprehensive analysis of AI code editors in 2026")
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# Check status (returns results when complete)
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deep_researcher_check(researchId: "<id from start>")
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```
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## Usage Patterns
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### Quick Lookup
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```
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web_search_exa(query: "Node.js 22 new features", numResults: 3)
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```
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### Code Research
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```
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get_code_context_exa(query: "Rust error handling patterns Result type", tokensNum: 3000)
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```
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### Company Due Diligence
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```
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company_research_exa(companyName: "Vercel", numResults: 5)
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web_search_advanced_exa(query: "Vercel funding valuation 2026", numResults: 3)
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```
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### Technical Deep Dive
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```
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# Start async research
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deep_researcher_start(query: "WebAssembly component model status and adoption")
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# ... do other work ...
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deep_researcher_check(researchId: "<id>")
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```
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## Tips
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- Use `web_search_exa` for broad queries, `web_search_advanced_exa` for filtered results
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- Lower `tokensNum` (1000-2000) for focused code snippets, higher (5000+) for comprehensive context
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- Combine `company_research_exa` with `web_search_advanced_exa` for thorough company analysis
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- Use `crawling_exa` to get full content from specific URLs found in search results
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- `deep_researcher_start` is best for comprehensive topics that benefit from AI synthesis
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## Related Skills
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- `deep-research` — Full research workflow using firecrawl + exa together
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- `market-research` — Business-oriented research with decision frameworks
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