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web-search-exa网络搜索 ex

Agent Skill

web-search-exa 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

973,381

周安装

40,156

GitHub Stars

44

下载量

318,036
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:web-search-exa(网络搜索 ex)
来源仓库:https://github.com/theishangoswami/web-search-exa
安装命令:
openclaw skills install web-search-exa
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install web-search-exa

简介

用于查找、检索和筛选相关信息,适合在OpenClaw中快速定位候选结果。

  • 通过Exa MCP服务器进行神经网络搜索和内容提取,支持深度研究。
  • 通过clawhub安装,结合来源仓库和原始README核验具体用法。
  • 安装前需确认权限范围、维护状态及是否触发联网或命令执行。
  • web-search-exa 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

name
web-search-exa
description
Neural web search, content extraction, company and people research, code search, and deep research via the Exa MCP server. Use when you need to: (1) search the web with semantic understanding — not just keywords, (2) find research papers, news, tweets, companies, or people, (3) extract clean content from URLs, (4) find semantically similar pages to a known URL, (5) get code examples and documentation, (6) run deep multi-step research with a report, (7) get a quick synthesized answer with citations. NOT for: local file operations, non-web tasks, or anything that doesn't involve web search or content retrieval.

Exa — Neural Web Search & Research

Exa is a neural search engine. Unlike keyword-based search, it understands meaning — you describe the page you're looking for and it finds it. Returns clean, LLM-ready content with no scraping needed.

MCP server: https://mcp.exa.ai/mcp Free tier: generous rate limits, no key needed for basic tools API key: dashboard.exa.ai/api-keys — unlocks higher limits + all tools Docs: exa.ai/docs GitHub: github.com/exa-labs/exa-mcp-server

Setup

Add the MCP server to your agent config:

# OpenClaw
openclaw mcp add exa --url "https://mcp.exa.ai/mcp"

Or in any MCP config JSON:

{
  "mcpServers": {
    "exa": {
      "url": "https://mcp.exa.ai/mcp"
    }
  }
}

To unlock all tools and remove rate limits, append your API key:

https://mcp.exa.ai/mcp?exaApiKey=YOUR_EXA_KEY

To enable specific optional tools:

https://mcp.exa.ai/mcp?exaApiKey=YOUR_KEY&tools=web_search_exa,web_search_advanced_exa,people_search_exa,crawling_exa,company_research_exa,get_code_context_exa,deep_researcher_start,deep_researcher_check,deep_search_exa

Tool Reference

Default tools (available without API key)

ToolWhat it does
web_search_exaGeneral-purpose web search — clean content, fast
get_code_context_exaCode examples + docs from GitHub, Stack Overflow, official docs
company_research_exaCompany overview, news, funding, competitors

Optional tools (enable via tools param, need API key for some)

ToolWhat it does
web_search_advanced_exaFull-control search: domain filters, date ranges, categories, content modes
crawling_exaExtract full page content from a known URL — handles JS, PDFs, complex layouts
people_search_exaFind LinkedIn profiles, professional backgrounds, experts
deep_researcher_startKick off an async multi-step research agent → detailed report
deep_researcher_checkPoll status / retrieve results from deep research
deep_search_exaSingle-call deep search with synthesized answer + citations (needs API key)

web_search_exa

Fast general search. Describe what you're looking for in natural language.

Parameters:

  • query (string, required) — describe the page you want to find
  • numResults (int) — number of results, default 10
  • typeauto (best quality), fast (lower latency), deep (multi-step reasoning)
  • livecrawlfallback (default) or preferred (always fetch fresh)
  • contextMaxCharacters (int) — cap the returned content size
web_search_exa {
  "query": "blog posts about using vector databases for recommendation systems",
  "numResults": 8
}
web_search_exa {
  "query": "latest OpenAI announcements March 2026",
  "numResults": 5,
  "type": "fast"
}

web_search_advanced_exa

The power-user tool. Everything web_search_exa does, plus domain filters, date filters, category targeting, and content extraction modes.

Extra parameters beyond basic search:

ParameterTypeWhat it does
includeDomainsstring[]Only return results from these domains (max 1200)
excludeDomainsstring[]Block results from these domains
categorystringTarget content type — see table below
startPublishedDatestringISO date, results published after this
endPublishedDatestringISO date, results published before this
maxAgeHoursintContent freshness — 0 = always livecrawl, -1 = cache only, 24 = cache if <24h
contents.highlightsobjectExtractive snippets relevant to query. Set maxCharacters to control size
contents.textobjectFull page as clean markdown. Set maxCharacters to cap
contents.summaryobjectLLM-generated summary. Supports query and JSON schema for structured extraction

Categories:

CategoryBest for
companyCompany pages, LinkedIn company profiles
peopleLinkedIn profiles, professional bios, personal sites
research paperarXiv, academic papers, peer-reviewed research
newsCurrent events, journalism
tweetPosts from X/Twitter
personal siteBlogs, personal pages
financial reportSEC filings, earnings reports

Examples

Research papers:

web_search_advanced_exa {
  "query": "transformer architecture improvements for long-context windows",
  "category": "research paper",
  "numResults": 15,
  "contents": { "highlights": { "maxCharacters": 3000 } }
}

Company list building with structured extraction:

web_search_advanced_exa {
  "query": "Series A B2B SaaS companies in climate tech founded after 2022",
  "category": "company",
  "numResults": 25,
  "contents": {
    "summary": {
      "query": "company name, what they do, funding stage, location",
      "schema": {
        "type": "object",
        "properties": {
          "name": { "type": "string" },
          "description": { "type": "string" },
          "funding": { "type": "string" },
          "location": { "type": "string" }
        }
      }
    }
  }
}

People search — find candidates with specific profiles:

web_search_advanced_exa {
  "query": "machine learning engineers at fintech startups in NYC with experience in fraud detection",
  "category": "people",
  "numResults": 20,
  "contents": { "highlights": { "maxCharacters": 2000 } }
}

Finding pages similar to a known URL: Use the URL itself as the query — Exa will find semantically similar pages:

web_search_advanced_exa {
  "query": "https://linkedin.com/in/some-candidate-profile",
  "numResults": 15,
  "contents": { "highlights": { "maxCharacters": 2000 } }
}

Recent news with freshness control:

web_search_advanced_exa {
  "query": "AI regulation policy updates",
  "category": "news",
  "maxAgeHours": 72,
  "numResults": 10,
  "contents": { "highlights": { "maxCharacters": 4000 } }
}

Scoped domain search:

web_search_advanced_exa {
  "query": "authentication best practices",
  "includeDomains": ["owasp.org", "auth0.com", "docs.github.com"],
  "numResults": 10,
  "contents": { "text": { "maxCharacters": 5000 } }
}

company_research_exa

One-call company research. Returns business overview, recent news, funding, and competitive landscape.

company_research_exa { "query": "Stripe payments company overview and recent news" }
company_research_exa { "query": "what does Anduril Industries do and who are their competitors" }

people_search_exa

Find professionals by role, company, location, expertise. Returns LinkedIn profiles and bios.

people_search_exa { "query": "VP of Engineering at healthcare startups in San Francisco" }
people_search_exa { "query": "AI researchers specializing in multimodal models" }

get_code_context_exa

Search GitHub repos, Stack Overflow, and documentation for code examples and API usage patterns.

get_code_context_exa { "query": "how to implement rate limiting in Express.js with Redis" }
get_code_context_exa { "query": "Python asyncio connection pooling example with aiohttp" }

crawling_exa

Extract clean content from a specific URL. Handles JavaScript-rendered pages, PDFs, and complex layouts. Returns markdown.

crawling_exa { "url": "https://arxiv.org/abs/2301.07041" }

Good for when you already have the URL and want to read the page.


deep_researcher_start + deep_researcher_check

Long-running async research. Exa's research agent searches, reads, and compiles a detailed report.

Start a research task:

deep_researcher_start {
  "query": "competitive landscape of AI code generation tools in 2026 — key players, pricing, technical approaches, market share"
}

Check status (use the researchId from the start response):

deep_researcher_check { "researchId": "abc123..." }

Poll deep_researcher_check until status is completed. The final response includes the full report.


deep_search_exa

Single-call deep search: expands your query across multiple angles, searches, reads results, and returns a synthesized answer with grounded citations. Requires API key.

deep_search_exa { "query": "what are the leading approaches to multimodal RAG in production systems" }

Supports structured output via outputSchema:

deep_search_exa {
  "query": "top 10 aerospace companies by revenue",
  "type": "deep",
  "outputSchema": {
    "type": "object",
    "required": ["companies"],
    "properties": {
      "companies": {
        "type": "array",
        "items": {
          "type": "object",
          "properties": {
            "name": { "type": "string" },
            "revenue": { "type": "string" },
            "hq": { "type": "string" }
          }
        }
      }
    }
  }
}

Query Craft

Exa is neural — it matches on meaning, not keywords. Write queries like you'd describe the ideal page to a colleague.

Do: "blog post about using embeddings for product recommendations at scale" Don't: "embeddings product recommendations"

Do: "Stripe payments company San Francisco fintech" Don't: "Stripe" (too ambiguous)

  • Use category when you know the content type — it makes a big difference.
  • For broader coverage, run 2-3 query variations in parallel and deduplicate results.
  • For agentic workflows, use highlights instead of full text — it's 10x more token-efficient while keeping the relevant parts.

Token Efficiency

Content modeWhen to use
highlightsAgent workflows, factual lookups, multi-step pipelines — most token-efficient
textDeep analysis, when you need full page context
summaryQuick overviews, structured extraction with JSON schema

Set maxCharacters on any content mode to control output size.

When to Reach for Which Tool

I need to...Use
Quick web lookupweb_search_exa
Research papers, academic searchweb_search_advanced_exa + category: "research paper"
Company intel, competitive analysiscompany_research_exa or advanced + category: "company"
Find people, candidates, expertspeople_search_exa or advanced + category: "people"
Code examples, API docsget_code_context_exa
Read a specific URLcrawling_exa
Find pages similar to a URLweb_search_advanced_exa with URL as query
Recent news / tweetsAdvanced + category: "news" or "tweet" + maxAgeHours
Detailed research reportdeep_researcher_startdeep_researcher_check
Quick answer with citationsdeep_search_exa

Docs: exa.ai/docsDashboard: dashboard.exa.aiSupport: support@exa.ai

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

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按下载量换算283,402

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安装前确认

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