Crawlora is a powerful platform designed for web scraping and data extraction. It helps users collect data from various websites for purposes like market research, competitor analysis, and lead generation. With user-friendly tools, advanced features, and strong support, Crawlora streamlines the data collection process, making it more efficient and effective. Whether you are a novice or an experienced data scientist, Crawlora offers the flexibility and power needed to handle complex data collection tasks seamlessly.

Stock Market Multi-Agent is an advanced open-source Python framework designed to streamline automated trading through coordinated AI agents. Each agent specializes in a specific function: Data Acquisition agents fetch and clean real-time market feeds, Signal Generation agents apply machine learning models for predictive insights, Backtesting agents rigorously evaluate strategies on historical datasets, Portfolio Management agents optimize asset allocation, Execution agents interface with brokerage APIs to place orders, and Risk Management agents enforce safeguards. The config-driven architecture allows plug-and-play modules, supporting customization of algorithms, data sources, and risk parameters. Suitable for research, live trading, and development, it accelerates quantitative strategy deployment and operational scalability.

Text Selected is a Chrome extension designed to enhance your web browsing experience. By simply selecting any text on a webpage and using the context menu option of Text Selected, the selected text is sent to a remote service that fetches relevant answers in real-time. This extension queries a JSON file hosted on Google Cloud Storage to find the best response to the selected text, which is then presented to the user in an alert. This tool is valuable for users seeking quick information and responses directly while navigating the web.

uAgents is a modular JavaScript framework that empowers developers to build autonomous, decentralized AI agents which can discover peers, exchange messages, collaborate on tasks, and adapt through learning. Agents communicate over libp2p-based gossip protocols, register capabilities via on-chain registries, and negotiate service-level agreements using smart contracts. The core library handles agent lifecycle events, message routing, and extensible behaviors such as reinforcement learning and market-driven task allocation. Through customizable plugins, uAgents can integrate with Fetch.ai’s ledger, external APIs, and oracle networks, enabling agents to perform real-world actions, data acquisition, and decision-making in distributed environments without centralized orchestration.

ToolAgents is a modular open-source AI agent framework that integrates large language models with external tools to automate complex workflows. Developers register tools via a centralized registry, defining endpoints for tasks such as API calls, database queries, code execution, and document analysis. Agents can plan multi-step operations, dynamically invoking or chaining tools based on LLM outputs. The framework supports both sequential and parallel task execution, error handling, and extensible plug-ins for custom tool integrations. With Python-based APIs, ToolAgents simplifies building, testing, and deploying intelligent agents that fetch data, generate content, execute scripts, and process documents, enabling rapid prototyping and scalable automation across analytics, research, and business operations.