exa-search 精选

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.

编码 Claude Code Codex CLI Cursor Gemini CLI MCP 客户端 MIT 28 万

在 GitHub 打开

安装方式

cp -r .agents/skills/exa-search ~/.claude/skills/exa-search

把该 skill 目录放进客户端 skills 目录。不同客户端的目录可能不同，Claude Code 默认是 ~/.claude/skills/

整仓一次性获取：git clone --depth 1 https://github.com/affaan-m/ECC.git

依赖与权限

需要 API Key —— 使用前需配置相应的密钥环境变量
需要联网访问外部服务
依赖外部命令：node python npx
以上为按正文与 frontmatter 自动推断的信号，仅供参考；安装前建议先阅读原文。

触发场景

code examplescompany intelpeople lookupAI-powered deep

SKILL.md 正文

来源 affaan-m/ECC@b92f181 · 许可 MIT · 内容未修改

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