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Open-source metasearch backend for AI agents

Open-source metasearch backend with AI search API for LLM agents, multi-engine aggregation, and structured JSON output.

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Open-Source Metasearch Backend for AI Agents

This open-source project provides a robust metasearch backend specifically designed for AI agents. It aggregates results from multiple search engines, offering a unified and structured API for Large Language Model (LLM) agents. This tool streamlines the process of information retrieval for developers building sophisticated AI applications that require broad and deep search capabilities. By abstracting away the complexities of individual search engine APIs, it allows agents to focus on interpreting and utilizing search results effectively.

What it Does

The core functionality of this metasearch backend is to act as a central hub for information gathering. It interfaces with various search engines, allowing AI agents to query a wide range of sources simultaneously. The system then aggregates, de-duplicates, and ranks the results before presenting them in a clean, structured JSON format. This ensures that LLM agents receive consistent and actionable data, regardless of the original source.

Key Features

Who it's For

This tool is ideal for AI developers , LLM engineers , and researchers who are building AI agents that require extensive and efficient information retrieval. It is particularly useful for projects involving: