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工具鏈接

  • Connery SDK enables developers to build, test, and deploy memory-enabled AI agents with tool integrations.
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    What is Connery SDK?
    Connery SDK is a comprehensive framework that simplifies the creation of AI agents. It provides client libraries for Node.js, Python, Deno, and the browser, enabling developers to define agent behaviors, integrate external tools and data sources, manage long-term memory, and connect to multiple LLMs. With built-in telemetry and deployment utilities, Connery SDK accelerates the entire agent lifecycle from development to production.
    Connery SDK Core Features
    • Multi-language client libraries (Node.js, Python, Deno, Browser)
    • Persistent memory stores for context retention
    • Multi-model and vector search integrations
    • Plugin and tool invocation framework
    • Built-in telemetry and logging
    • Deployment utilities for cloud and on-premises
    Connery SDK Pro & Cons

    The Cons

    Documentation indicates last update was 7 months ago, which may imply slower recent development.
    Lack of explicit pricing or enterprise support details might limit adoption for larger businesses.
    No mention of ready-made end-user applications or demo apps available.

    The Pros

    Open-source, facilitating transparency and community contributions.
    Combines SDK and CLI to streamline AI plugin and action development.
    Standardized REST API simplifies app integration and interaction consistency.
    Handles authorization, input validation, and logging automatically.
    Flexible plugin architecture enabling interaction with external services.
    Connery SDK Pricing
    Has free planNo
    Free trial details
    Pricing model
    Is credit card requiredNo
    Has lifetime planNo
    Billing frequency
    For the latest prices, please visit: https://docs.connery.io/sdk
  • An open-source REST API for defining, customizing, and deploying multi-tool AI agents for coursework and prototyping.
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    What is MIU CS589 AI Agent API?
    MIU CS589 AI Agent API offers a standardized interface for building custom AI agents. Developers can define agent behaviors, integrate external tools or services, and handle streaming or batch responses via HTTP endpoints. The framework handles authentication, request routing, error handling and logging out of the box. It is fully extensible—users can register new tools, adjust agent memory, and configure LLM parameters. Suitable for experimentation, demos, and production prototypes, it simplifies multi-tool orchestration and accelerates AI agent development without locking you into a monolithic platform.
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