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exa-apiEXA API 搜索

Agent Skill

用于辅助 API 设计、接口文档、请求响应结构和服务集成说明。它适合让 Agent 梳理 endpoint、生成 OpenAPI 草稿、检查字段命名、整理错误码或辅助前后端联调。使用时需要确认真实业务语义、鉴权方式、分页和错误处理规则;涉及生成接口文档时,应避免凭空补字段,最好从现有代码、schema 或接口样例中提取事实。

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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:exa-api(EXA API 搜索)
来源仓库:https://github.com/byungkyu/exa-api
安装命令:
openclaw skills install exa-api
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 exa-api

简介

exa-api 用于辅助 API 设计与集成说明,适合梳理接口结构与文档。

  • 适用于生成 OpenAPI 草稿、检查字段命名或协助前后端联调。
  • 通过 clawhub 安装,需结合来源仓库和 README 核验具体用法。
  • 使用时需确认真实业务语义、鉴权方式及错误处理规则。
  • 支持神经网络搜索、页面内容检索与 AI 答案生成功能。

SKILL.md

name
exa
description
|
metadata
author
maton
version
1.0
clawdbot
emoji
🧠
homepage
https://maton.ai
requires
env

Exa

Access the Exa API with managed API key authentication. Perform neural web searches, retrieve page contents, find similar pages, get AI-generated answers with citations, and run async research tasks.

Quick Start

# Search the web
python <<'EOF'
import urllib.request, os, json
data = json.dumps({"query": "latest AI research", "numResults": 5}).encode()
req = urllib.request.Request('https://gateway.maton.ai/exa/search', data=data, method='POST')
req.add_header('Authorization', f'Bearer {os.environ["MATON_API_KEY"]}')
req.add_header('Content-Type', 'application/json')
print(json.dumps(json.load(urllib.request.urlopen(req)), indent=2))
EOF

Base URL

https://gateway.maton.ai/exa/{endpoint}

Replace {endpoint} with the Exa API endpoint (search, contents, findSimilar, answer, research/v1). The gateway proxies requests to api.exa.ai and automatically injects your API key.

Authentication

All requests require the Maton API key in the Authorization header:

Authorization: Bearer $MATON_API_KEY

Environment Variable: Set your API key as MATON_API_KEY:

export MATON_API_KEY="YOUR_API_KEY"

Getting Your API Key

  1. Sign in or create an account at maton.ai
  2. Go to maton.ai/settings
  3. Copy your API key

Connection Management

Manage your Exa API key connections at https://ctrl.maton.ai.

List Connections

python <<'EOF'
import urllib.request, os, json
req = urllib.request.Request('https://ctrl.maton.ai/connections?app=exa&status=ACTIVE')
req.add_header('Authorization', f'Bearer {os.environ["MATON_API_KEY"]}')
print(json.dumps(json.load(urllib.request.urlopen(req)), indent=2))
EOF

Create Connection

python <<'EOF'
import urllib.request, os, json
data = json.dumps({'app': 'exa', 'method': 'API_KEY'}).encode()
req = urllib.request.Request('https://ctrl.maton.ai/connections', data=data, method='POST')
req.add_header('Authorization', f'Bearer {os.environ["MATON_API_KEY"]}')
req.add_header('Content-Type', 'application/json')
print(json.dumps(json.load(urllib.request.urlopen(req)), indent=2))
EOF

Open the returned url in a browser to enter your Exa API key.

Get Connection

python <<'EOF'
import urllib.request, os, json
req = urllib.request.Request('https://ctrl.maton.ai/connections/{connection_id}')
req.add_header('Authorization', f'Bearer {os.environ["MATON_API_KEY"]}')
print(json.dumps(json.load(urllib.request.urlopen(req)), indent=2))
EOF

Delete Connection

python <<'EOF'
import urllib.request, os, json
req = urllib.request.Request('https://ctrl.maton.ai/connections/{connection_id}', method='DELETE')
req.add_header('Authorization', f'Bearer {os.environ["MATON_API_KEY"]}')
print(json.dumps(json.load(urllib.request.urlopen(req)), indent=2))
EOF

Specifying Connection

If you have multiple Exa connections, specify which one to use with the Maton-Connection header:

python <<'EOF'
import urllib.request, os, json
data = json.dumps({"query": "AI news"}).encode()
req = urllib.request.Request('https://gateway.maton.ai/exa/search', data=data, method='POST')
req.add_header('Authorization', f'Bearer {os.environ["MATON_API_KEY"]}')
req.add_header('Content-Type', 'application/json')
req.add_header('Maton-Connection', '{connection_id}')
print(json.dumps(json.load(urllib.request.urlopen(req)), indent=2))
EOF

If omitted, the gateway uses the default (oldest) active connection.

API Reference

Search

Perform a neural web search with optional content extraction.

POST /exa/search
Content-Type: application/json

{
  "query": "latest AI research papers",
  "numResults": 10
}

Request Parameters:

ParameterTypeRequiredDescription
querystringYesSearch query string
numResultsintegerNoNumber of results (max 100, default 10)
typestringNoSearch type: neural, auto (default), keyword
categorystringNoFilter by category: company, research paper, news, tweet, personal site, financial report, people
includeDomainsarrayNoOnly include these domains
excludeDomainsarrayNoExclude these domains
startPublishedDatestringNoISO 8601 date filter (after)
endPublishedDatestringNoISO 8601 date filter (before)
contentsobjectNoContent extraction options (see below)

Contents Options:

{
  "contents": {
    "text": true,
    "highlights": true,
    "summary": true
  }
}
OptionTypeDescription
textboolean/objectExtract full page text
highlightsboolean/objectExtract relevant snippets
summaryboolean/objectGenerate AI summary

Response:

{
  "requestId": "abc123",
  "resolvedSearchType": "neural",
  "results": [
    {
      "id": "https://example.com/article",
      "title": "Article Title",
      "url": "https://example.com/article",
      "publishedDate": "2024-01-15T00:00:00.000Z",
      "author": "Author Name",
      "text": "Full page content...",
      "highlights": ["Relevant snippet 1", "Relevant snippet 2"],
      "summary": "AI-generated summary..."
    }
  ],
  "costDollars": {
    "total": 0.005
  }
}

Get Contents

Retrieve full page contents for specific URLs.

POST /exa/contents
Content-Type: application/json

{
  "ids": ["https://example.com/page1", "https://example.com/page2"],
  "text": true
}

Request Parameters:

ParameterTypeRequiredDescription
idsarrayYesList of URLs to fetch content from
textbooleanNoInclude full page text
highlightsboolean/objectNoInclude relevant snippets
summaryboolean/objectNoGenerate AI summary

Response:

{
  "requestId": "abc123",
  "results": [
    {
      "id": "https://example.com/page1",
      "url": "https://example.com/page1",
      "title": "Page Title",
      "text": "Full page content..."
    }
  ]
}

Find Similar

Find pages similar to a given URL.

POST /exa/findSimilar
Content-Type: application/json

{
  "url": "https://example.com",
  "numResults": 10
}

Request Parameters:

ParameterTypeRequiredDescription
urlstringYesURL to find similar pages for
numResultsintegerNoNumber of results (max 100, default 10)
includeDomainsarrayNoOnly include these domains
excludeDomainsarrayNoExclude these domains
contentsobjectNoContent extraction options

Response:

{
  "requestId": "abc123",
  "results": [
    {
      "id": "https://similar-site.com",
      "title": "Similar Site",
      "url": "https://similar-site.com",
      "score": 0.95
    }
  ],
  "costDollars": {
    "total": 0.005
  }
}

Answer

Get an AI-generated answer to a question with citations.

POST /exa/answer
Content-Type: application/json

{
  "query": "What is machine learning?",
  "text": true
}

Request Parameters:

ParameterTypeRequiredDescription
querystringYesQuestion to answer
textbooleanNoInclude source text in response

Response:

{
  "requestId": "abc123",
  "answer": "Machine learning is a subset of artificial intelligence...",
  "citations": [
    {
      "id": "https://example.com/ml-guide",
      "url": "https://example.com/ml-guide",
      "title": "Machine Learning Guide"
    }
  ]
}

Research Tasks

Run asynchronous research tasks that explore the web, gather sources, and synthesize findings with citations.

Create Research Task

POST /exa/research/v1
Content-Type: application/json

{
  "instructions": "What are the top AI companies and their main products?",
  "model": "exa-research"
}

Request Parameters:

ParameterTypeRequiredDescription
instructionsstringYesWhat to research (max 4096 chars)
modelstringNoModel to use: exa-research-fast, exa-research (default), exa-research-pro
outputSchemaobjectNoJSON Schema for structured output

Response:

{
  "researchId": "r_01abc123",
  "createdAt": 1772969504083,
  "model": "exa-research",
  "instructions": "What are the top AI companies...",
  "status": "running"
}

Get Research Task

GET /exa/research/v1/{researchId}

Query Parameters:

ParameterTypeDescription
eventsstringSet to true to include event log
streamstringSet to true for SSE streaming

Response (completed):

{
  "researchId": "r_01abc123",
  "status": "completed",
  "createdAt": 1772969504083,
  "finishedAt": 1772969520000,
  "model": "exa-research",
  "instructions": "What are the top AI companies...",
  "output": {
    "content": "Based on my research, the top AI companies are..."
  },
  "costDollars": {
    "total": 0.15,
    "numSearches": 5,
    "numPages": 20,
    "reasoningTokens": 1500
  }
}

Status values: pending, running, completed, canceled, failed

List Research Tasks

GET /exa/research/v1?limit=10

Query Parameters:

ParameterTypeDescription
limitintegerResults per page (1-50, default 10)
cursorstringPagination cursor

Response:

{
  "data": [
    {
      "researchId": "r_01abc123",
      "status": "completed",
      "model": "exa-research",
      "instructions": "What are the top AI companies..."
    }
  ],
  "hasMore": false,
  "nextCursor": null
}

Code Examples

JavaScript

// Search with content extraction
const response = await fetch('https://gateway.maton.ai/exa/search', {
  method: 'POST',
  headers: {
    'Authorization': `Bearer ${process.env.MATON_API_KEY}`,
    'Content-Type': 'application/json'
  },
  body: JSON.stringify({
    query: 'latest AI news',
    numResults: 5,
    contents: { text: true, highlights: true }
  })
});
const data = await response.json();

Python

import os
import requests

# Search with content extraction
response = requests.post(
    'https://gateway.maton.ai/exa/search',
    headers={'Authorization': f'Bearer {os.environ["MATON_API_KEY"]}'},
    json={
        'query': 'latest AI news',
        'numResults': 5,
        'contents': {'text': True, 'highlights': True}
    }
)
data = response.json()

Notes

  • Search types: neural (semantic), auto (hybrid), keyword (traditional)
  • Maximum 100 results per search request
  • Content extraction (text, highlights, summary) incurs additional costs
  • Categories like people and company have restricted filter support
  • Timestamps are in ISO 8601 format
  • IMPORTANT: When piping curl output to jq or other commands, environment variables like $MATON_API_KEY may not expand correctly in some shell environments

Error Handling

StatusMeaning
400Missing Exa connection or invalid request
401Invalid or missing Maton API key
429Rate limited
4xx/5xxPassthrough error from Exa API

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