Discover free AI agents built for Research: Comprehensive directory of solutions verified by AI agency professionals focused on the Research sector.

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AlphaEvolve is an evolutionary AI coding agent developed by Google DeepMind, designed to autonomously discover and optimize complex algorithms across various domains. Leveraging the capabilities of Gemini 2.5 Flash and Pro models, AlphaEvolve employs an ensemble approach that balances computational throughput with solution quality. It utilizes an evolutionary framework where large language models generate candidate algorithms, which are then evaluated and refined through automated processes. This system has achieved notable successes, including surpassing the 56-year-old Strassen algorithm for matrix multiplication and optimizing data center scheduling, leading to significant efficiency gains. AlphaEvolve's ability to generate provably novel and correct algorithms marks a significant advancement in AI-driven scientific discovery.

AlphaEvolve

alphaevolve

A Gemini-powered AI coding agent that autonomously discovers and optimizes complex algorithms.

Google's AI Co-Scientist is a multi-agent system built on Gemini 2.0, designed to function as a virtual scientific collaborator. It assists researchers by generating novel hypotheses, designing experiments, and analyzing complex datasets. The system employs specialized agents that mimic the scientific method through processes like generation, reflection, and ranking. In collaboration with institutions like Stanford University and Imperial College London, the AI Co-Scientist has demonstrated its ability to identify novel biological mechanisms and potential therapeutic targets, showcasing its potential to accelerate scientific and biomedical discoveries.

Google AI Co-Scientist

google-ai-co-scientist

A multi-agent AI system that collaborates with scientists to generate hypotheses and accelerate biomedical research.

Agent Network Protocol (ANP) is an open-source communication protocol designed to facilitate secure, decentralized interactions among AI agents. It aims to become the 'HTTP of the Agentic Web Era' by providing a standardized framework that enables agents to connect, communicate, and collaborate efficiently. ANP's architecture comprises three layers: the Identity Layer for decentralized authentication using W3C DID standards, the Meta-Protocol Layer for dynamic protocol negotiation, and the Application Layer for semantic-based capability descriptions. This structure ensures interoperability, scalability, and secure communication across diverse AI systems.

Agent Network Protocol

agent-network-protocol

An open-source protocol enabling secure, decentralized communication among AI agents.

Crawl4AI is an open-source, LLM-friendly web crawler and scraper designed to streamline web data extraction for AI agents and data pipelines. It offers features such as asynchronous crawling, structured data output in formats like JSON and Markdown, and integration capabilities with large language models. Crawl4AI supports advanced extraction strategies, including LLM-based methods, and provides tools for handling dynamic content, making it a versatile solution for developers seeking efficient and customizable web scraping solutions.

Crawl4AI

crawl4ai

An open-source, LLM-friendly web crawler and scraper optimized for AI agents and data pipelines.

Dcup is an open-source, self-hostable Retrieval-Augmented Generation (RAG) platform designed to help developers and teams build scalable, AI-powered retrieval pipelines. It enables seamless integration with data sources like Google Drive, Dropbox, and AWS, and supports advanced search capabilities including LLM re-ranking, summary indexing, and hybrid search using OpenAI embeddings and Qdrant vector storage. With its intuitive Retrieval API and modular architecture, Dcup simplifies the process of ingesting, indexing, and retrieving data, making it ideal for AI applications requiring efficient and accurate information retrieval.

Dcup

dcup

An open-source RAG-as-a-Service platform for building scalable, AI-powered retrieval pipelines.

Codex CLI is an open-source, terminal-native AI coding assistant developed by OpenAI. Designed for developers who prefer working directly in the terminal, it integrates OpenAI's latest models (like o4-mini) to perform tasks such as reading, modifying, and executing code within a local environment. Codex CLI supports multimodal inputs, allowing users to pass text, screenshots, or diagrams to generate or edit code accordingly. It offers three distinct approval modes—Suggest, Auto Edit, and Full Auto—providing flexibility in how autonomous the agent operates. The tool emphasizes security by running in a sandboxed, network-disabled environment and ensures that your source code remains on your machine unless explicitly shared. With zero-setup installation and compatibility with macOS, Linux, and experimental support for Windows via WSL, Codex CLI aims to streamline the development workflow by bringing powerful AI capabilities directly to the command line.

Codex CLI

codex-cli

Open-source terminal-based AI coding assistant that reads, writes, and executes code locally with multimodal input support.

Cerebrum is the Software Development Kit (SDK) for AIOS, the AI Agent Operating System. It provides developers with tools to build, deploy, and manage large language model (LLM)-based AI agents. Cerebrum addresses challenges such as scheduling, context switching, memory management, and tool integration, facilitating the creation of efficient and scalable AI agents. The SDK features a modular architecture encompassing LLM, memory, storage, and tool management layers, and includes an Agent Hub for sharing and discovering agents with version control and dependency management.

Cerebrum: AIOS SDK

cerebrum-aios-sdk

An SDK for developing and deploying LLM-based AI agents within the AIOS framework.

The Capability Collaboration based AI Agent (CACA Agent) is an AI system designed to enhance the extensibility and functionality of AI agents by integrating a set of collaborative capabilities. Inspired by service computing, it reduces reliance on a single large language model (LLM) and promotes an open architecture. CACA Agent introduces components such as Planning Capability, Methodology Capability, Tools Capability, Tool Broker, and Tool Service, which work together to provide AI agent functionalities. This design facilitates quick deployment of AI agents and convenient expansion of their application scenarios, allowing for dynamic tool integration and improved planning abilities. A demonstration of the system illustrates its operation and the extension of application scenarios.

CACA Agent

caca-agent

An AI system enhancing agent extensibility through collaborative capabilities.

PC Agent is an AI system developed by GAIR-NLP that facilitates the creation of autonomous digital agents by transferring human cognitive processes. It comprises three key components: PC Tracker, a lightweight infrastructure for collecting large-scale human-computer interaction data; a Cognition Completion post-processing pipeline that converts raw interaction data into cognitive trajectories; and a multi-agent system combining a planning agent for decision-making with a grounding agent for robust visual grounding. PC Agent aims to enable AI to perform complex digital tasks autonomously by learning from human interactions.

PC Agent

pc-agent

An AI system enabling autonomous digital agents through human cognition transfer.

AutoGLM Rumination is an AI agent developed by Zhipu AI, capable of performing deep research and tasks such as web searches, travel planning, and research report writing. Powered by Zhipu's proprietary models, including GLM-Z1-Air and GLM-4-Air-0414, it offers enhanced performance and efficiency. The agent is available for free through Zhipu's official channels, including their website and mobile app.

AutoGLM Rumination

autoglm-rumination

A free AI agent by Zhipu AI for deep research and autonomous task execution.

Roo Code is an open-source autonomous AI agent designed to code, debug, and evolve software systems with minimal human input. It mimics a junior developer's workflow, using a cyclic process of planning, editing, running, and debugging code. Roo Code supports multi-turn coding sessions and automatically persists context across iterations. It is built on top of a task memory system, supports integration with your terminal and development environment, and is designed for continuous improvement through natural interactions.

Roo Code

roo-code

An autonomous open-source AI agent that can code, debug, and evolve software with minimal human intervention.

Gemma 3 is Google's latest open-source AI model, designed to run efficiently on a single GPU or TPU. It supports multimodal inputs, including text, images, and short videos, and offers advanced reasoning capabilities. With support for over 140 languages and a 128k-token context window, Gemma 3 is versatile for various applications. Its quantized versions enhance performance and reduce computational requirements, making it accessible for devices ranging from smartphones to workstations.

Gemma 3

gemma-3

An open-source AI model optimized for single-GPU performance, supporting multimodal inputs and over 140 languages.

AI Agents for "Research" Industry, free pricing