Tavily Search

Tavily API integration with managed API key authentication. Perform AI-powered web search, extract content from URLs, crawl websites, map site structure, and run research tasks. Use this skill when users want to search the web, extract page content, crawl websites, discover URLs, or conduct in-depth research with citations. For other third party apps, use the api-gateway skill (https://clawhub.ai/byungkyu/api-gateway). Requires network access and valid Maton API key.

Tavily

Access the Tavily API with managed API key authentication. Perform AI-powered web searches, extract content from URLs, crawl websites, map site structure, and run in-depth research tasks.

Quick Start

bash

# Search the web
python <<'EOF'
import urllib.request, os, json
data = json.dumps({"query": "latest AI news", "max_results": 5}).encode()
req = urllib.request.Request('https://gateway.maton.ai/tavily/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

text

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

Replace {endpoint} with the Tavily API endpoint (search, extract, crawl, map, research). The gateway proxies requests to api.tavily.com and automatically injects your API key.

Authentication

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

text

Authorization: Bearer $MATON_API_KEY

Environment Variable: Set your API key as MATON_API_KEY:

bash

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 Tavily API key connections at https://ctrl.maton.ai.

List Connections

bash

python <<'EOF'
import urllib.request, os, json
req = urllib.request.Request('https://ctrl.maton.ai/connections?app=tavily&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

bash

python <<'EOF'
import urllib.request, os, json
data = json.dumps({'app': 'tavily', '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 Tavily API key.

Get Connection

bash

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

bash

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 Tavily connections, specify which one to use with the Maton-Connection header:

bash

python <<'EOF'
import urllib.request, os, json
data = json.dumps({"query": "AI news"}).encode()
req = urllib.request.Request('https://gateway.maton.ai/tavily/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 AI-powered web search with optional answer generation.

bash

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

{
  "query": "What is artificial intelligence?",
  "max_results": 5
}

Request Parameters:

Parameter	Type	Required	Description
query	string	Yes	Search query string
max_results	integer	No	Number of results (0-20, default 5)
search_depth	string	No	basic, advanced, fast, ultra-fast (default: basic)
topic	string	No	general or news (default: general)
include_answer	boolean/string	No	true, false, basic, advanced
include_raw_content	boolean/string	No	true, false, markdown, text
include_images	boolean	No	Include image results
include_domains	array	No	Only search these domains (max 300)
exclude_domains	array	No	Exclude these domains (max 150)
time_range	string	No	day, week, month, year
start_date	string	No	Filter by date (YYYY-MM-DD)
end_date	string	No	Filter by date (YYYY-MM-DD)

Response:

json

{
  "query": "What is artificial intelligence?",
  "answer": "Artificial intelligence (AI) is...",
  "results": [
    {
      "title": "What is AI?",
      "url": "https://example.com/ai",
      "content": "AI is a branch of computer science...",
      "score": 0.95
    }
  ],
  "response_time": 0.55
}

Extract

Extract content from one or more URLs.

bash

POST /tavily/extract
Content-Type: application/json

{
  "urls": ["https://example.com/article"],
  "format": "markdown"
}

Request Parameters:

Parameter	Type	Required	Description
urls	string/array	Yes	URL or array of URLs to extract
query	string	No	User intent for reranking content
chunks_per_source	integer	No	Max chunks per source (1-5, default 3)
extract_depth	string	No	basic or advanced (default: basic)
format	string	No	markdown or text (default: markdown)
include_images	boolean	No	Include extracted images
timeout	float	No	Max wait time in seconds (1-60)

Response:

json

{
  "results": [
    {
      "url": "https://example.com/article",
      "raw_content": "# Article Title\n\nContent in markdown...",
      "images": [],
      "favicon": "https://example.com/favicon.ico"
    }
  ],
  "failed_results": [],
  "response_time": 0.01
}

Map

Discover URLs from a website without extracting content.

bash

POST /tavily/map
Content-Type: application/json

{
  "url": "https://example.com",
  "limit": 20
}

Request Parameters:

Parameter	Type	Required	Description
url	string	Yes	Root URL to begin mapping
instructions	string	No	Natural language guidance for crawler
max_depth	integer	No	Exploration depth (1-5, default 1)
max_breadth	integer	No	Links per page level (1-500, default 20)
limit	integer	No	Total links to process (default 50)
select_paths	array	No	Regex patterns for URL inclusion
exclude_paths	array	No	Regex patterns for URL exclusion
allow_external	boolean	No	Include external links (default true)
timeout	float	No	Max wait time (10-150 seconds)

Response:

json

{
  "base_url": "https://example.com",
  "results": [
    "https://example.com/about",
    "https://example.com/products",
    "https://example.com/contact"
  ],
  "response_time": 0.1
}

Crawl

Crawl a website and extract content from discovered pages.

bash

POST /tavily/crawl
Content-Type: application/json

{
  "url": "https://example.com",
  "limit": 10,
  "max_depth": 2
}

Request Parameters:

Parameter	Type	Required	Description
url	string	Yes	Root URL to begin crawl
instructions	string	No	Natural language guidance (2x cost)
chunks_per_source	integer	No	Max snippets per source (1-5, default 3)
max_depth	integer	No	Exploration depth (1-5, default 1)
max_breadth	integer	No	Links per page level (1-500, default 20)
limit	integer	No	Total links to process (default 50)
select_paths	array	No	Regex patterns for URL inclusion
exclude_paths	array	No	Regex patterns for URL exclusion
allow_external	boolean	No	Include external links (default true)
extract_depth	string	No	basic or advanced (default: basic)
format	string	No	markdown or text (default: markdown)
timeout	float	No	Max wait time (10-150 seconds)

Response:

json

{
  "base_url": "https://example.com",
  "results": [
    {
      "url": "https://example.com/about",
      "raw_content": "# About Us\n\nContent...",
      "favicon": "https://example.com/favicon.ico"
    }
  ],
  "response_time": 0.09
}

Research Tasks

Run async research tasks that gather sources and synthesize findings.

Create Research Task

bash

POST /tavily/research
Content-Type: application/json

{
  "input": "What are the latest developments in AI safety?",
  "model": "mini"
}

Request Parameters:

Parameter	Type	Required	Description
input	string	Yes	Research task or question
model	string	No	mini, pro, or auto (default: auto)
stream	boolean	No	Stream results via SSE (default: false)
output_schema	object	No	JSON Schema for structured output
citation_format	string	No	numbered, mla, apa, chicago

Response:

json

{
  "request_id": "582a6eec-9a10-43ba-830f-d9a1aeb19f07",
  "status": "pending",
  "input": "What are the latest developments in AI safety?",
  "model": "mini",
  "created_at": "2026-03-08T11:36:12.674507+00:00",
  "response_time": 0.05
}

Get Research Task

bash

GET /tavily/research/{request_id}

Response (completed):

json

{
  "request_id": "582a6eec-9a10-43ba-830f-d9a1aeb19f07",
  "status": "completed",
  "content": "## AI Safety Developments\n\nResearch findings...",
  "sources": [
    {
      "title": "Source Title",
      "url": "https://example.com/source",
      "favicon": "https://example.com/favicon.ico"
    }
  ],
  "created_at": "2026-03-08T11:36:12.674507+00:00",
  "response_time": 45
}

Status values: pending, in_progress, completed, failed

Code Examples

JavaScript

javascript

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

Python

python

import os
import requests

# Search with answer
response = requests.post(
    'https://gateway.maton.ai/tavily/search',
    headers={'Authorization': f'Bearer {os.environ["MATON_API_KEY"]}'},
    json={
        'query': 'latest AI news',
        'max_results': 5,
        'include_answer': True
    }
)
data = response.json()

Notes

• Search endpoints return AI-generated answers when include_answer is enabled
• Map returns URLs only; Crawl returns URLs with extracted content
• Using instructions parameter in crawl/map doubles the credit cost
• Research tasks are async - poll with GET to check status
• Research models: mini (fast/efficient), pro (comprehensive)
• 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

Status	Meaning
400	Missing Tavily connection or invalid request
401	Invalid or missing Maton API key
429	Rate limit exceeded
432	Plan limit exceeded
433	Pay-as-you-go limit exceeded
4xx/5xx	Passthrough error from Tavily API

Resources

• Tavily API Documentation
• Search API Reference
• Extract API Reference
• Crawl API Reference
• Research API Reference
• Tavily Dashboard
• Maton Community
• Maton Support