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31 dépôts

Awesome GitHub RepositoriesProtocols and Interoperability

Explore 31 awesome GitHub repositories matching artificial intelligence & ml · Protocols and Interoperability. Refine with filters or upvote what's useful.

Awesome Protocols and Interoperability GitHub Repositories

Trouvez les meilleurs dépôts grâce à l'IA.Nous recherchons les dépôts les plus pertinents grâce à l'IA.
  • openclaw/openclawAvatar de openclaw

    openclaw/openclaw

    380,031Voir sur GitHub↗

    Openclaw est une plateforme de gestion d'environnements d'exécution d'agents, fournissant l'infrastructure nécessaire pour contrôler les cycles de vie des agents, l'état des sessions et la persistance des espaces de travail. Elle dispose d'une passerelle centralisée qui gère les boucles de modèles, l'invocation d'outils et les événements en streaming, tout en prenant en charge le routage multi-agents et la gestion de la mémoire persistante. Le système est conçu pour normaliser les signatures d'exécution des outils et fournir une interface standardisée pour la compatibilité entre les fournisseurs. La plateforme inclut des outils de développement étendus, tels qu'une interface en ligne de commande pour la gestion des espaces de travail, la journalisation de diagnostic et une architecture de plugins qui permet l'enregistrement d'outils et de capacités personnalisés. Elle prend en charge les flux de travail automatisés via des hooks pilotés par les événements, la planification des tâches et l'intégration avec des services externes. La sécurité est gérée par des politiques d'exécution, la portabilité des identifiants et des flux de travail d'approbation pour les actions des agents. Le déploiement est pris en charge par des installateurs d'infrastructure automatisés et des assistants de passerelle conteneurisés, avec des utilitaires intégrés pour les sauvegardes et la gestion de la configuration. Le système fournit un format structuré pour orchestrer des flux de travail en plusieurs étapes et inclut des outils spécialisés pour l'automatisation des navigateurs et le patch de code structuré.

    Registers executable tools for model access while enforcing strict allowlisting and validation protocols.

    TypeScriptaiassistantcrustacean
    Voir sur GitHub↗380,031
  • anomalyco/opencodeAvatar de anomalyco

    anomalyco/opencode

    175,152Voir sur GitHub↗

    OpenCode is a framework for orchestrating autonomous AI agents within development environments. It provides a multi-tiered architecture where primary assistants manage user interaction while specialized subagents handle specific tasks like planning, research, and code generation. The system includes a comprehensive command-line interface for managing these workflows, configuring agent behavior, and defining custom tools or commands through metadata-rich files. The platform features a modular plugin system and extensive integration support, including standardized protocols for connecting local

    Regulates tool availability for agents using pattern-based filtering and specific execution settings.

    TypeScript
    Voir sur GitHub↗175,152
  • modelcontextprotocol/serversAvatar de modelcontextprotocol

    modelcontextprotocol/servers

    87,320Voir sur GitHub↗

    The Model Context Protocol is a standardized communication framework designed to connect language models to external data sources, functional tools, and interactive user interfaces. It provides a vendor-neutral interface layer that enables AI hosts to discover and execute capabilities across heterogeneous service environments, using a JSON-RPC based messaging standard to facilitate bidirectional communication between clients and servers. The protocol distinguishes itself through a robust capability-based handshake that negotiates feature sets during session initialization, ensuring compatibil

    Offers structured, read-only access to files, databases, or API documentation for retrieving and supplying relevant context.

    TypeScript
    Voir sur GitHub↗87,320
  • a2aproject/a2aAvatar de a2aproject

    a2aproject/A2A

    24,404Voir sur GitHub↗

    A2A is a standardized framework designed to enable interoperability, discovery, and orchestration among independent artificial intelligence agents. It provides a common communication protocol that allows heterogeneous agents to exchange data, verify identities, and collaborate across diverse programming languages and computing environments. By establishing a unified messaging standard, the project facilitates the creation of complex, multi-agent workflows where tasks are routed and managed between specialized services. The project distinguishes itself through a capability-based architecture t

    Advertises support for specific protocol extensions within agent profiles, allowing clients to discover and request specialized interaction patterns beyond the core standard.

    Shella2aa2a-mcpa2a-protocol
    Voir sur GitHub↗24,404
  • prefecthq/fastmcpAvatar de PrefectHQ

    PrefectHQ/fastmcp

    22,994Voir sur GitHub↗

    FastMCP is a Python framework designed for building servers that expose functions, resources, and prompts to AI models using the Model Context Protocol. It simplifies the development process by automatically deriving tool metadata, input schemas, and documentation directly from Python function signatures and type hints. The framework provides a unified container for managing these components, allowing developers to build modular applications that integrate seamlessly with AI assistants. The project distinguishes itself through its support for interactive, server-defined user interface compone

    Wraps Python functions into protocol-compliant tools and resources that allow language models to interact with external logic.

    Pythonagentsfastmcpllms
    Voir sur GitHub↗22,994
  • vercel/aiAvatar de vercel

    vercel/ai

    21,885Voir sur GitHub↗

    This project is a comprehensive framework for building AI-powered applications, providing a unified toolkit for orchestrating language models, autonomous agents, and interactive user interfaces. It serves as a central library for managing the entire lifecycle of AI interactions, from initial prompt generation and model provider abstraction to complex, multi-step reasoning and tool execution. The framework distinguishes itself through its deep integration with frontend development, specifically by enabling generative user interfaces that render dynamic components directly from model outputs. I

    Enables dynamic requests for structured user input or confirmation during tool execution flows.

    TypeScriptanthropicartificial-intelligencegemini
    Voir sur GitHub↗21,885
  • modelcontextprotocol/python-sdkAvatar de modelcontextprotocol

    modelcontextprotocol/python-sdk

    21,729Voir sur GitHub↗

    The Model Context Protocol SDK is a framework for building clients and servers that connect AI models to external data, tools, and resources using a standardized communication protocol. It provides the foundational libraries and interfaces necessary to establish reliable, transport-agnostic connections between AI agents and external systems, enabling seamless information retrieval and task automation. The SDK distinguishes itself through a robust capability negotiation handshake that ensures compatibility between connected parties before exchanging messages. It supports a pluggable transport

    Implements a standardized, transport-agnostic protocol for AI agent interoperability and context retrieval.

    Python
    Voir sur GitHub↗21,729
  • automaapp/automaAvatar de AutomaApp

    AutomaApp/automa

    21,425Voir sur GitHub↗

    Automa is a browser-based automation platform that enables users to build, schedule, and execute repetitive web tasks through a visual, no-code interface. By operating as a browser extension, it provides a canvas-based environment where users construct workflows by connecting functional blocks to interact with web elements, manage browser state, and process data. The platform distinguishes itself through its deep integration with the browser environment, allowing for complex orchestration such as event-driven triggers, cross-origin request handling, and the ability to package workflows as sta

    Displays interactive prompts during execution to collect necessary data from users.

    Vueautomationbrowser-automationbrowser-extension
    Voir sur GitHub↗21,425
  • containerd/containerdAvatar de containerd

    containerd/containerd

    20,369Voir sur GitHub↗

    Containerd is a daemon-based container runtime that manages the complete lifecycle of containers on a host system. It functions as a core orchestration backend, handling image distribution, storage, and process execution while adhering to industry-standard specifications for container execution and configuration. The project is distinguished by its modular, plugin-based architecture, which allows for the extension of storage, runtime, and networking capabilities without requiring a full daemon recompile. It utilizes a shim-based execution model to delegate low-level operations, ensuring isola

    Standardizes how hardware like GPUs are described and accessed by containers to ensure consistent resource availability.

    Gocncfcontainerdcontainers
    Voir sur GitHub↗20,369
  • livekit/livekitAvatar de livekit

    livekit/livekit

    19,358Voir sur GitHub↗

    LiveKit is a comprehensive framework for building and orchestrating real-time, multimodal AI agents that interact with users through voice, video, and text. It provides a centralized, event-driven architecture to manage the entire lifecycle of automated participants, from initialization and session state management to graceful shutdown. By utilizing a selective forwarding unit, the platform efficiently routes media streams between participants and agents, ensuring low-latency communication and secure, token-based authentication for all connections. The platform distinguishes itself through it

    Prompts users for birth information and normalizes spoken or written formats into structured data.

    Gogolangmedia-serversfu
    Voir sur GitHub↗19,358
  • emcie-co/parlantAvatar de emcie-co

    emcie-co/parlant

    18,119Voir sur GitHub↗

    Parlant is an agentic workflow engine and orchestration framework designed for building conversational AI that adheres to strict behavioral guidelines. It provides a platform for managing multi-turn interactions through state-machine-based logic, allowing developers to define complex, hierarchical conversational flows that can adapt, skip, or revisit steps based on real-time user input. The framework distinguishes itself through its focus on behavioral governance and observability. It enables developers to define precise domain terminology and enforce instruction compliance through prioritize

    Prompts users to clarify requests when input is unclear to ensure the agent selects the correct action.

    Pythonai-agentsai-alignmentcustomer-service
    Voir sur GitHub↗18,119
  • kilo-org/kilocodeAvatar de Kilo-Org

    Kilo-Org/kilocode

    15,616Voir sur GitHub↗

    Kilocode is an autonomous engineering platform designed to orchestrate AI agents for complex software development tasks. It functions as a comprehensive system for automating coding, testing, and repository management by integrating directly with your codebase and terminal. The platform provides a unified gateway for model orchestration, allowing for the management of agentic workflows, event-driven automation, and persistent session state across distributed development environments. The platform distinguishes itself through its federated task management and policy-based access control, which

    Queries users for missing information or preferences to resolve ambiguity during task execution.

    TypeScriptaiai-ageai-coding
    Voir sur GitHub↗15,616
  • modelcontextprotocol/typescript-sdkAvatar de modelcontextprotocol

    modelcontextprotocol/typescript-sdk

    12,674Voir sur GitHub↗

    This project provides a TypeScript software development kit for the Model Context Protocol, a standard designed to facilitate bidirectional communication between AI applications and external data sources or tools. It serves as a foundational framework for building both clients and servers, enabling language models to interact with external systems through a unified, decoupled interface. The SDK distinguishes itself by implementing a transport-agnostic connection layer that supports both local standard input-output streams and remote HTTP endpoints. It utilizes a JSON-RPC message bus to manage

    Enables servers to prompt users for structured data or external actions during automated task execution.

    TypeScript
    Voir sur GitHub↗12,674
  • web-infra-dev/midsceneAvatar de web-infra-dev

    web-infra-dev/midscene

    11,720Voir sur GitHub↗

    Midscene is a multimodal automation framework designed to enable AI agents to perceive, navigate, and manipulate graphical user interfaces across web, mobile, and desktop environments. By leveraging vision-capable AI models, the platform interprets interface screenshots to execute tasks based on natural language instructions, removing the reliance on traditional, brittle code-based selectors. The framework distinguishes itself through its ability to decompose high-level goals into autonomous, multi-step sequences that function consistently across diverse platforms. It provides a visual ground

    Exposes automation capabilities as standard tools for AI agents to inspect and interact with interfaces.

    TypeScriptaiai-testbrowser-use
    Voir sur GitHub↗11,720
  • spectreconsole/spectre.consoleAvatar de spectreconsole

    spectreconsole/spectre.console

    11,210Voir sur GitHub↗

    Spectre.Console is a .NET framework designed for building structured, feature-rich command-line applications. It provides a comprehensive toolkit for managing complex command hierarchies, type-safe argument parsing, and dependency injection, allowing developers to decouple business logic from input processing while maintaining modular application designs. The framework distinguishes itself through a sophisticated terminal user interface toolkit that enables the creation of dynamic, interactive console experiences. It utilizes a markup-based rendering system to display styled text, tables, cha

    Collects text, single-choice selections, and multiple-choice selections from the user to drive interactive command-line workflows and configuration wizards.

    C#ansi-colorscli-parserconsole
    Voir sur GitHub↗11,210
  • livekit/agentsAvatar de livekit

    livekit/agents

    9,379Voir sur GitHub↗

    This project is a framework for developing multimodal AI agents that function as programmable participants in real-time communication rooms. It enables the construction of agents that can see, hear, and speak by integrating speech-to-text, large language models, and text-to-speech pipelines to facilitate low-latency, natural conversations. The system is distinguished by its advanced orchestration of real-time media and conversational flow, including support for full-duplex speech, preemptive response generation, and sophisticated interruption management. It further differentiates itself throu

    Prompts for and normalizes date and time of birth data from conversational input.

    Pythonagentsaiopenai
    Voir sur GitHub↗9,379
  • modelcontextprotocol/inspectorAvatar de modelcontextprotocol

    modelcontextprotocol/inspector

    8,721Voir sur GitHub↗

    The inspector is a diagnostic and validation tool for the Model Context Protocol. It provides an interactive interface and a transport proxy to discover, inspect, and execute the tools, prompts, and resources provided by an MCP server. The project serves as a debugger and compliance tester to verify that server implementations adhere to the protocol specification and JSON-RPC standards. It allows for real-time monitoring of message exchanges and logs between clients and servers across various transport layers, such as standard input/output and Server-Sent Events. The tool covers a broad rang

    Collects required structured data from clients to satisfy requests during the execution of asynchronous tasks.

    TypeScript
    Voir sur GitHub↗8,721
  • modelcontextprotocol/modelcontextprotocolAvatar de modelcontextprotocol

    modelcontextprotocol/modelcontextprotocol

    8,458Voir sur GitHub↗

    Model Context Protocol is a standardized framework for connecting large language models to external data sources and executable tools. It enables the creation of a universal interface where servers expose tools, resources, and prompts that can be discovered and utilized by various AI clients. The protocol utilizes a JSON-RPC message system that is transport-agnostic, supporting both standard input/output for local processes and HTTP with server-sent events for remote connections. It emphasizes security and control by delegating model sampling to the client to keep API keys secure from servers

    Requests additional information or clarification from the user to complete specific processes.

    TypeScript
    Voir sur GitHub↗8,458
  • lastmile-ai/mcp-agentAvatar de lastmile-ai

    lastmile-ai/mcp-agent

    8,037Voir sur GitHub↗

    mcp-agent is a framework for building AI agents that integrate with Model Context Protocol servers to execute tools and access data. It functions as a multi-agent orchestrator and protocol-compliant server, enabling the creation of agents that can discover and invoke tools from connected external servers. The project distinguishes itself through a durable workflow engine that supports long-running tasks capable of pausing, resuming, and surviving restarts. It implements complex orchestration patterns, including iterative evaluator-optimizer loops, hierarchical workflow nesting, and specialist

    Prompts end-users for personal credentials through a scoped configuration flow.

    Pythonagentsaiai-agents
    Voir sur GitHub↗8,037
  • plopjs/plopAvatar de plopjs

    plopjs/plop

    7,666Voir sur GitHub↗

    Plop is a template-based code generator and interactive command-line scaffolding tool. It functions as a file system automation engine that uses a pipeline of prompt-driven tasks and regular expression replacements to generate and modify codebase structures. The framework combines Handlebars templates with interactive terminal prompts to automate boilerplate code generation. It allows for the enforcement of codebase patterns through shared generators and provides the ability to embed the engine into custom command-line tools. The system covers the creation of project files from templates and

    Gathers data through interactive terminal prompts using various input types and plugins.

    JavaScriptcligeneratorjavascript
    Voir sur GitHub↗7,666
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  1. Home
  2. Artificial Intelligence & ML
  3. Agentic Systems Frameworks
  4. Protocols and Interoperability

Explorer les sous-tags

  • AI Protocol Extensions1 sous-tagStandardized interfaces and communication protocols for extending AI agent capabilities and interoperability.
  • Agent Tool RegistriesMechanisms for defining and registering executable tools that allow AI models to interact with external systems or perform specific tasks.
  • MCP Server Controls1 sous-tagMechanisms for managing and filtering tool availability for AI agents.
  • Resource Exposure Frameworks2 sous-tagsStandardized interfaces that allow external systems to discover and access specific machine learning resources.
  • Tool Exposure Frameworks1 sous-tagFrameworks that enable machine learning models to safely interact with and utilize external software tools.
  • User Interaction Protocols1 sous-tagStandardized methods for managing how users provide input and interact with artificial intelligence systems.