Agent Gallery

Nimble Agent Discovery APIs help you find and understand available agents before using them. Browse agents by vertical, search by domain, and inspect detailed schemas to understand input parameters and output fields.

Can’t find what you need? Create a custom agent for any website using the Agentic Studio - no coding required, just describe what you want in natural language.

All public agents are maintained by Nimble - we monitor them 24/7 and automatically update them when websites change their structure.

Explore Agent Gallery

Browse agents visually with previews, examples, and interactive documentation.

When to Use

Use agent discovery when you need to:

Browse available agents - See what platforms are supported
Filter by vertical - Find agents for specific industries (e-commerce, search, social)
Inspect agent details - Understand input parameters and output schema
Check capabilities - Verify localization and pagination support

Two Ways to Explore

Via Platform UI

Browse agents visually with previews, examples, and interactive documentation.

Browse pre-built agents with visual previews and documentation

Explore agent details including schemas, descriptions, and interactive demos

Run a live test and export the validated code snippet to your development environment

Via API

Programmatically discover and inspect agents for automation and integration.

List Agents API

Browse and search the agent catalog.

GET https://sdk.nimbleway.com/v1/agents

Parameters

Parameter	Type	Description	Required
`privacy`	Enum	Filter by privacy level (`all`, `public`, `private`)	No
`offset`	Integer	Pagination offset (default: `0`)	No
`limit`	Integer	Number of results per page (default: `100`)	No

Response Schema

Each agent in the response contains:

Field	Type	Description
`name`	string	Unique agent identifier (use this in API calls)
`display_name`	string	Human-readable agent name
`description`	string	What the agent does
`is_public`	boolean	Whether the agent is maintained by Nimble
`vertical`	string	Industry vertical (e.g., “Ecommerce”, “Search”)
`entity_type`	string	Page type (e.g., “Product Detail Page”, “SERP”)
`domain`	string	Target website domain

Usage Examples

from nimble_sdk import NimbleClient

client = NimbleClient(api_key="YOUR-API-KEY")

# List all public agents
agents = client.agents.list(privacy="public")

for agent in agents:
    print(f"{agent['name']}: {agent['display_name']}")
    print(f"  Domain: {agent['domain']}")
    print(f"  Vertical: {agent['vertical']}")
    print(f"  Type: {agent['entity_type']}")

Response Example

[
  {
    "name": "amazon_pdp",
    "is_public": true,
    "display_name": "Amazon Product Page",
    "description": "Extract structured data from Amazon product detail pages including pricing, reviews, specifications, and availability.",
    "vertical": "Ecommerce",
    "entity_type": "Product Detail Page (PDP)",
    "domain": "www.amazon.com"
  },
  {
    "name": "amazon_serp",
    "is_public": true,
    "display_name": "Amazon Search Results",
    "description": "Extract product listings from Amazon search results pages based on a keyword query.",
    "vertical": "Ecommerce",
    "entity_type": "Search Engine Results Page (SERP)",
    "domain": "www.amazon.com"
  },
  {
    "name": "walmart_pdp",
    "is_public": true,
    "display_name": "Walmart Product Page",
    "description": "Extract structured data from Walmart product detail pages including pricing, reviews, and variants.",
    "vertical": "Ecommerce",
    "entity_type": "Product Detail Page (PDP)",
    "domain": "www.walmart.com"
  },
  {
    "name": "google_search",
    "is_public": true,
    "display_name": "Google Search Results",
    "description": "Extract structured data from Google Search Results Pages (SERPs) including organic results, ads, and featured snippets.",
    "vertical": "Search Engine",
    "entity_type": "Search Engine Results Page (SERP)",
    "domain": "www.google.com"
  }
]

Get Agent Details API

Get comprehensive information about a specific agent, including input parameters and output schema.

GET https://sdk.nimbleway.com/v1/agents/{agent_name}

Parameters

Parameter	Type	Description	Required
`agent_name`	string	The agent name (e.g., `amazon_pdp`)	Yes

Response Schema

Field	Type	Description
`name`	string	Unique agent identifier
`display_name`	string	Human-readable agent name
`description`	string	What the agent does
`is_public`	boolean	Whether maintained by Nimble
`vertical`	string	Industry vertical
`entity_type`	string	Page type
`domain`	string	Target website domain
`input_properties`	array	Input parameters for the agent (see below)
`output_schema`	object	JSON schema describing output fields
`feature_flags`	object	Supported capabilities (localization, pagination)

Input Properties

Each item in input_properties contains:

Field	Type	Description
`name`	string	Parameter name
`type`	string	Data type (string, number, boolean)
`description`	string	What the parameter does
`required`	boolean	Whether the parameter is required
`default`	string	Default value if not provided
`examples`	array	Example values
`rules`	array	Validation rules

Feature Flags

Flag	Type	Description
`is_localization_supported`	boolean	Supports ZIP code for location-specific data
`is_pagination_supported`	boolean	Supports paginated results

Usage Examples

from nimble_sdk import NimbleClient

client = NimbleClient(api_key="YOUR-API-KEY")

# Get agent details
agent = client.agents.get("amazon_pdp")

print(f"Agent: {agent['display_name']}")
print(f"Description: {agent['description']}")
print(f"Domain: {agent['domain']}")

# Check feature flags
flags = agent['feature_flags']
print(f"\nCapabilities:")
print(f"  Localization: {'Yes' if flags['is_localization_supported'] else 'No'}")
print(f"  Pagination: {'Yes' if flags['is_pagination_supported'] else 'No'}")

# List input parameters
print(f"\nInput Parameters:")
for param in agent['input_properties']:
    required = "required" if param['required'] else "optional"
    print(f"  {param['name']} ({param['type']}) - {required}")
    print(f"    {param['description']}")
    if param.get('examples'):
        print(f"    Examples: {', '.join(param['examples'])}")

Response Example

{
  "name": "amazon_pdp",
  "is_public": true,
  "display_name": "Amazon Product Page",
  "description": "Extract structured data from Amazon product detail pages including pricing, reviews, specifications, variants, and availability.",
  "vertical": "Ecommerce",
  "entity_type": "Product Detail Page (PDP)",
  "domain": "www.amazon.com",
  "input_properties": [
    {
      "name": "asin",
      "required": true,
      "type": "string",
      "description": "Amazon Standard Identification Number (ASIN) - the unique 10-character product identifier",
      "rules": ["Must be exactly 10 alphanumeric characters"],
      "examples": ["B08N5WRWNW", "B0DLKFK6LR"],
      "default": null
    },
    {
      "name": "zip_code",
      "required": false,
      "type": "string",
      "description": "ZIP code for location-specific pricing and availability",
      "rules": ["5-digit US ZIP code"],
      "examples": ["90210", "10001"],
      "default": "90210"
    }
  ],
  "output_schema": {
    "asin": { "type": "string", "description": "Product ASIN" },
    "product_title": { "type": "string", "description": "Full product name" },
    "brand": { "type": "string", "description": "Product brand" },
    "web_price": { "type": "number", "description": "Current selling price" },
    "list_price": { "type": "number", "description": "Original price before discount" },
    "average_of_reviews": { "type": "number", "description": "Average rating (0-5)" },
    "number_of_reviews": { "type": "number", "description": "Total review count" },
    "availability": { "type": "boolean", "description": "Whether in stock" },
    "image_url": { "type": "string", "description": "Main product image URL" }
  },
  "feature_flags": {
    "is_localization_supported": true,
    "is_pagination_supported": false
  }
}

Available Agents by Vertical

E-commerce

Agent	Display Name	Domain	Localization	Pagination
`amazon_pdp`	Amazon Product Page	www.amazon.com	Yes	No
`amazon_serp`	Amazon Search	www.amazon.com	Yes	Yes
`amazon_category`	Amazon Category	www.amazon.com	No	Yes
`walmart_pdp`	Walmart Product Page	www.walmart.com	Yes	No
`walmart_search`	Walmart Search	www.walmart.com	Yes	Yes
`target_pdp`	Target Product Page	www.target.com	Yes	No
`best_buy_pdp`	Best Buy Product	www.bestbuy.com	Yes	No
`home_depot_pdp`	Home Depot Product	www.homedepot.com	Yes	No

Search Engines

Agent	Display Name	Domain	Localization	Pagination
`google_search`	Google Search Results	www.google.com	Yes	Yes
`google_maps_search`	Google Maps Search	maps.google.com	Yes	Yes
`google_search_aio`	Google AI Overview	www.google.com	Yes	No

Agent	Display Name	Domain	Localization	Pagination
`tiktok_account`	TikTok Account	www.tiktok.com	No	Yes
`facebook_page`	Facebook Page	www.facebook.com	No	No
`youtube_shorts`	YouTube Shorts	www.youtube.com	No	Yes

LLM Platforms

Agent	Display Name	Domain	Localization	Pagination
`chatgpt`	ChatGPT Responses	chatgpt.com	No	No
`gemini`	Gemini Responses	gemini.google.com	No	No
`perplexity`	Perplexity	www.perplexity.ai	No	No
`grok`	Grok Responses	grok.com	No	No

Common Patterns

Filter Agents by Vertical

Find all agents for a specific industry:

from nimble_sdk import NimbleClient

client = NimbleClient(api_key="YOUR-API-KEY")

# Get all agents
agents = client.agents.list(privacy="public")

# Filter by vertical
ecommerce_agents = [
    agent for agent in agents
    if agent.get('vertical') == 'Ecommerce'
]

print(f"Found {len(ecommerce_agents)} e-commerce agents:")
for agent in ecommerce_agents:
    print(f"  {agent['name']}: {agent['display_name']} ({agent['domain']})")

Check Localization Support

Verify an agent supports location-specific data:

from nimble_sdk import NimbleClient

client = NimbleClient(api_key="YOUR-API-KEY")

agent = client.agents.get("amazon_pdp")

if agent['feature_flags']['is_localization_supported']:
    print("This agent supports localization!")
    print("Pass zip_code parameter for location-specific pricing.")
else:
    print("This agent does not support localization.")

Get Required Parameters

Find which parameters are required before calling an agent:

from nimble_sdk import NimbleClient

client = NimbleClient(api_key="YOUR-API-KEY")

agent = client.agents.get("amazon_pdp")

required_params = [
    p for p in agent['input_properties']
    if p['required']
]

optional_params = [
    p for p in agent['input_properties']
    if not p['required']
]

print("Required parameters:")
for p in required_params:
    examples = ', '.join(p.get('examples', []))
    print(f"  {p['name']}: {p['description']}")
    if examples:
        print(f"    Examples: {examples}")

print("\nOptional parameters:")
for p in optional_params:
    default = p.get('default', 'none')
    print(f"  {p['name']}: {p['description']} (default: {default})")

Validate Parameters Before Calling

Check parameters match the expected schema:

from nimble_sdk import NimbleClient

client = NimbleClient(api_key="YOUR-API-KEY")

def validate_params(agent_name, params):
    """Validate params against agent input_properties"""
    agent = client.agents.get(agent_name)
    errors = []

    # Build lookup of input properties
    props = {p['name']: p for p in agent['input_properties']}

    # Check required fields
    for prop_name, prop in props.items():
        if prop['required'] and prop_name not in params:
            errors.append(f"Missing required parameter: {prop_name}")

    # Check for unknown parameters
    for param_name in params:
        if param_name not in props:
            errors.append(f"Unknown parameter: {param_name}")

    return errors

# Validate before calling
errors = validate_params("amazon_pdp", {"asin": "B08N5WRWNW"})

if errors:
    print("Validation errors:")
    for error in errors:
        print(f"  - {error}")
else:
    print("Parameters are valid!")

Next Steps

Use Agents

Learn how to call agents in your code

E-commerce Agents

Explore e-commerce agent capabilities

Create Custom Agent

Build your own agent with natural language

Platform Gallery

Browse agents visually

Introduction

Web Tools

Agentic

Explore Agent Gallery

When to Use

Two Ways to Explore

Via Platform UI

Via API

List Agents API

Parameters

Response Schema

Usage Examples

Response Example

Get Agent Details API

Parameters

Response Schema

Input Properties

Feature Flags

Usage Examples

Response Example

Available Agents by Vertical

E-commerce

Search Engines

LLM Platforms

Common Patterns

Filter Agents by Vertical

Check Localization Support

Get Required Parameters

Validate Parameters Before Calling

Next Steps

Use Agents

E-commerce Agents

Create Custom Agent

Platform Gallery

Introduction

Web Tools

Agentic

Explore Agent Gallery

​When to Use

​Two Ways to Explore

​Via Platform UI

​Via API

​List Agents API

​Parameters

​Response Schema

​Usage Examples

​Response Example

​Get Agent Details API

​Parameters

​Response Schema

​Input Properties

​Feature Flags

​Usage Examples

​Response Example

​Available Agents by Vertical

​E-commerce

​Search Engines

​Social Media

​LLM Platforms

​Common Patterns

​Filter Agents by Vertical

​Check Localization Support

​Get Required Parameters

​Validate Parameters Before Calling

​Next Steps

Use Agents

E-commerce Agents

Create Custom Agent

Platform Gallery

When to Use

Two Ways to Explore

Via Platform UI

Via API

List Agents API

Parameters

Response Schema

Usage Examples

Response Example

Get Agent Details API

Parameters

Response Schema

Input Properties

Feature Flags

Usage Examples

Response Example

Available Agents by Vertical

E-commerce

Search Engines

Social Media

LLM Platforms

Common Patterns

Filter Agents by Vertical

Check Localization Support

Get Required Parameters

Validate Parameters Before Calling

Next Steps