Showing 4 open source projects for "network discovery visualisation"

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  • 1
    Materials Discovery: GNoME

    Materials Discovery: GNoME

    AI discovers 520000 stable inorganic crystal structures for research

    Materials Discovery (GNoME) is a large-scale research initiative by Google DeepMind focused on applying graph neural networks to accelerate the discovery of stable inorganic crystal materials. The project centers on Graph Networks for Materials Exploration (GNoME), a message-passing neural network architecture trained on density functional theory (DFT) data to predict material stability and energy formation.
    Downloads: 5 This Week
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  • 2
    Klavis AI

    Klavis AI

    MCP integration platforms for AI agents to use tools at any scale

    Klavis AI is a Y Combinator X25-backed open-source infrastructure platform that enables AI agents to reliably connect with external tools and services at scale through Model Context Protocol (MCP). Founded by ex-Google DeepMind and ex-Lyft engineers, Klavis provides 50+ production-ready MCP servers with enterprise OAuth support for GitHub, Slack, Gmail, Salesforce, Linear, Notion, and more. The flagship product Strata solves tool overload through progressive discovery, achieving +13% higher...
    Downloads: 2 This Week
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  • 3
    PentestAgent

    PentestAgent

    AI agent framework for black-box security testing

    PentestAgent is an open-source autonomous security testing platform designed to help organizations identify vulnerabilities and assess security posture by simulating real-world attack scenarios without manual intervention. It brings a modular and automated approach to penetration testing by orchestrating a suite of tools and scripts that can emulate common exploitation techniques, reconnaissance workflows, and post-exploitation activities across targets. Users configure rules, policies, and...
    Downloads: 5 This Week
    Last Update:
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  • 4
    Integuru v0

    Integuru v0

    The first AI agent that builds permissionless integrations

    Integuru is an open-source AI agent designed to automatically create integrations between software platforms by reverse-engineering their internal APIs. Instead of relying on official developer documentation or publicly available APIs, the system analyzes network traffic generated by user interactions within a web application. Developers capture browser requests and authentication data, which the agent then uses to infer the structure of the platform’s internal API endpoints. Based on this...
    Downloads: 1 This Week
    Last Update:
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