Showing 4 open source projects for "common"

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    Universal Commerce Protocol (UCP)

    Universal Commerce Protocol (UCP)

    The common language for platforms, agents and businesses.

    Universal Commerce Protocol (UCP) is an open standard designed to unify how platforms, businesses, and payment providers interact across the modern commerce ecosystem. It provides a common language that eliminates fragmented, custom integrations and enables seamless interoperability between diverse commerce systems. Built for an increasingly agentic web, UCP supports AI-driven platforms that can discover products, manage carts, and complete transactions securely on a user’s behalf. Its modular, capability-based architecture allows businesses to expose only what they support while remaining flexible and extensible. ...
    Downloads: 2 This Week
    Last Update:
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  • 2
    Kheish

    Kheish

    Kheish: A multi-role LLM agent for tasks like code auditing

    Kheish is a framework designed for cybersecurity professionals to automate penetration testing tasks, providing tools to streamline security assessments.
    Downloads: 5 This Week
    Last Update:
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  • 3
    kagent

    kagent

    Kubernetes native framework for building AI agents

    ...It supports multiple model providers through a dedicated configuration resource, allowing teams to switch providers or run mixed environments while keeping the agent spec stable. A major focus is tool integration via MCP: agents can connect to MCP servers for tool access, and kagent includes an MCP server with tools for common Kubernetes and platform engineering systems.
    Downloads: 0 This Week
    Last Update:
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  • 4
    Koog

    Koog

    Koog is the official Kotlin framework for building AI agents

    ...It features pure Kotlin implementation, seamless Model Control Protocol (MCP) integration for enhanced model management, vector embeddings for semantic search, and a flexible system for creating and extending tools that access external systems and APIs. Ready‑to‑use components address common AI engineering challenges, while intelligent history compression optimizes token usage and preserves context. A powerful streaming API enables real‑time response processing and parallel tool calls. Persistent memory allows agents to retain knowledge across sessions and between agents, and comprehensive tracing facilities provide detailed debugging and monitoring.
    Downloads: 0 This Week
    Last Update:
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