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exa-search

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 A…

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技能内容

Exa Search

Neural search for web content, code, companies, and people via the Exa MCP server.

When to Activate

  • User needs current web information or news
  • Searching for code examples, API docs, or technical references
  • Researching companies, competitors, or market players
  • Finding professional profiles or people in a domain
  • Running background research for any development task
  • User says "search for", "look up", "find", or "what's the latest on"

MCP Requirement

Exa MCP server must be configured. Add to ~/.claude.json:

"exa-web-search": {
  "command": "npx",
  "args": ["-y", "exa-mcp-server"],
  "env": { "EXA_API_KEY": "YOUR_EXA_API_KEY_HERE" }
}

Get an API key at exa.ai.

Core Tools

web_search_exa

General web search for current information, news, or facts.

web_search_exa(query: "latest AI developments 2026", numResults: 5)

Parameters:

| Param | Type | Default | Notes |

|-------|------|---------|-------|

| query | string | required | Search query |

| numResults | number | 8 | Number of results |

web_search_advanced_exa

Filtered search with domain and date constraints.

web_search_advanced_exa(
  query: "React Server Components best practices",
  numResults: 5,
  includeDomains: ["github.com", "react.dev"],
  startPublishedDate: "2025-01-01"
)

Parameters:

| Param | Type | Default | Notes |

|-------|------|---------|-------|

| query | string | required | Search query |

| numResults | number | 8 | Number of results |

| includeDomains | string[] | none | Limit to specific domains |

| excludeDomains | string[] | none | Exclude specific domains |

| startPublishedDate | string | none | ISO date filter (start) |

| endPublishedDate | string | none | ISO date filter (end) |

get_code_context_exa

Find code examples and documentation from GitHub, Stack Overflow, and docs sites.

get_code_context_exa(query: "Python asyncio patterns", tokensNum: 3000)

Parameters:

| Param | Type | Default | Notes |

|-------|------|---------|-------|

| query | string | required | Code or API search query |

| tokensNum | number | 5000 | Content tokens (1000-50000) |

company_research_exa

Research companies for business intelligence and news.

company_research_exa(companyName: "Anthropic", numResults: 5)

Parameters:

| Param | Type | Default | Notes |

|-------|------|---------|-------|

| companyName | string | required | Company name |

| numResults | number | 5 | Number of results |

people_search_exa

Find professional profiles and bios.

people_search_exa(query: "AI safety researchers at Anthropic", numResults: 5)

crawling_exa

Extract full page content from a URL.

crawling_exa(url: "https://example.com/article", tokensNum: 5000)

Parameters:

| Param | Type | Default | Notes |

|-------|------|---------|-------|

| url | string | required | URL to extract |

| tokensNum | number | 5000 | Content tokens |

deep_researcher_start / deep_researcher_check

Start an AI research agent that runs asynchronously.

# Start research
deep_researcher_start(query: "comprehensive analysis of AI code editors in 2026")

# Check status (returns results when complete)
deep_researcher_check(researchId: "<id from start>")

Usage Patterns

Quick Lookup

web_search_exa(query: "Node.js 22 new features", numResults: 3)

Code Research

get_code_context_exa(query: "Rust error handling patterns Result type", tokensNum: 3000)

Company Due Diligence

company_research_exa(companyName: "Vercel", numResults: 5)
web_search_advanced_exa(query: "Vercel funding valuation 2026", numResults: 3)

Technical Deep Dive

# Start async research
deep_researcher_start(query: "WebAssembly component model status and adoption")
# ... do other work ...
deep_researcher_check(researchId: "<id>")

Tips

  • Use web_search_exa for broad queries, web_search_advanced_exa for filtered results
  • Lower tokensNum (1000-2000) for focused code snippets, higher (5000+) for comprehensive context
  • Combine company_research_exa with web_search_advanced_exa for thorough company analysis
  • Use crawling_exa to get full content from specific URLs found in search results
  • deep_researcher_start is best for comprehensive topics that benefit from AI synthesis

Related Skills

  • deep-research — Full research workflow using firecrawl + exa together
  • market-research — Business-oriented research with decision frameworks

想直接用这个技能?

本站把开放许可(MIT / Apache 等)的技能按仓库打包整理到网盘,点一下转存到你自己的网盘,不用一个个从 GitHub 拉。许可未声明的技能只给原始仓库链接,不打包。

同名技能的其他版本

有 4 个不同仓库或目录里都有叫 exa-search 的技能。它们内容并不相同,别混用:

  • affaan-m/ECC — Exa MCPによるウェブ、コード、企業調査のためのニューラル検索。ユーザーがウェブ検索、コード例、企業情報、人物検索、またはExaのニューラル検索エンジンを使ったAI駆動の詳細調
  • affaan-m/ECC — 通过Exa MCP进行神经搜索,适用于网络、代码和公司研究。当用户需要网络搜索、代码示例、公司情报、人员查找,或使用Exa神经搜索引擎进行AI驱动的深度研究时使用。
  • affaan-m/ECC — Neural search via Exa MCP for web, code, and company research. Use when the user needs web