AutoSERP is a search-powered data collection tool that uses AI to extract specific data from Google search results. You can automate searches, customize workflows, and integrate it with your APIs and webhooks. It’s designed for developers looking to gather data efficiently without using crawlers or writing code.
Features
API + Webhooks
The API allows you to either retrieve search results directly or stream them in real-time, providing flexibility. With webhook support, you can send data to any endpoint, making it easy to integrate into existing systems and workflows.
Powered as RAG
Enhance Retrieval-Augmented Generation (RAG) workflows by integrating with your LLM. The feature facilitates automatic search, parsing, and fixes relevant data into your model in real-time, ensuring highly accurate information.
Search Query Syntax
Advanced syntax for constructing search queries that include AND, OR operators, exact match, exclusion, site search, and date range filters to refine search results.
Customizable Schemas
Allows users to define the structure of the extracted data by setting schemas to ensure data consistency and validity according to user-defined specifications.
Process Endpoint
Allows users to submit URLs for processing through a simple API call. This feature is essential for integrating with various applications and workflows.
Webhook Integration
Provides the ability to receive notifications for completed processes through webhooks. Users can set up endpoints to automatically handle the responses.
Rate Limits
Includes mechanisms to control the number of requests processed per minute and day. This helps manage and optimize API usage efficiently.
Fetch Task Results
Enables users to retrieve the results of processed tasks via API. This feature supports the integration of output results into user-defined applications.
Code Examples
Offers sample code in different programming languages, including Python, to facilitate easier integration and implementation for developers.