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

# 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

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:

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

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

Connection Management

Manage your Tavily 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=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

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

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 Tavily 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/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.

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:

{
  "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.

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:

{
  "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.

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:

{
  "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.

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:

{
  "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

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:

{
  "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

GET /tavily/research/{request_id}

Response (completed):

{
  "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

// 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

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 |

Tavily Search

Tavily

Quick Start

Base URL

Authentication

Getting Your API Key

Connection Management

List Connections

Create Connection

Get Connection

Delete Connection

Specifying Connection

API Reference

Search

Extract

Map

Crawl

Research Tasks

Create Research Task

Get Research Task

Code Examples

JavaScript

Python

Notes

Error Handling

Resources