Awesome GitHub RepositoriesFunction-to-Tool Converters

This project is a Python framework for building autonomous, event-driven agent systems. It provides a unified runtime for orchestrating multi-agent workflows, managing persistent conversation state, and executing code within secure, isolated sandbox environments. The framework is designed to handle complex task delegation, allowing agents to invoke other agents as tools while maintaining context across multi-turn interactions. The framework distinguishes itself through its deep integration with the Model Context Protocol, enabling agents to connect to external data sources and remote services

The Gemini Cookbook is a comprehensive collection of implementation patterns, code samples, and development guides designed for building applications with Google Gemini models. It serves as a central resource for developers to integrate multimodal generative artificial intelligence into their software, providing the necessary frameworks to manage model interactions, stateful workflows, and structured data extraction. The repository distinguishes itself by offering specialized toolkits for autonomous agent orchestration, enabling the construction of agents that can execute code, browse the web

Pipecat is a framework and software development kit for building real-time multimodal AI agents and speech-to-speech systems. It utilizes a frame-based data pipeline to route audio, video, and text through a modular sequence of processors, enabling the orchestration of low-latency conversational AI. The project is distinguished by its ability to coordinate complex multimodal services, including speech-to-text, language models, and text-to-speech, within a single pipeline. It features semantic voice activity detection for natural turn-taking, state-machine conversation flows for dialogue manag

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

Claude-engineer is an autonomous software engineering agent and command-line interface for interacting with the Claude 3.5 Sonnet model. It functions as an AI code editor that writes code, manages local files, and executes terminal commands to automate technical workflows. The system features a self-evolving tool framework that allows the agent to design and implement its own functional scripts to expand its capabilities during a session. It utilizes a sandboxed Python executor to run scripts for data analysis and complex computations in a secure remote environment. The project covers a broa

Tambo is an orchestration platform and framework designed for building generative user interfaces and conversational AI agents. It provides the infrastructure to manage persistent chat threads, execute multi-step reasoning workflows, and integrate large language models with external tools and services. By combining an agent orchestration layer with a component-based library, the project enables developers to create interactive interfaces where AI models dynamically render and update UI elements in real-time. The framework distinguishes itself through its generative UI capabilities, which allo

This project is a comprehensive Node.js software development kit designed for integrating large language models into applications. It serves as a foundational client for interacting with REST and WebSocket services, enabling developers to implement chat functionality, multimodal content generation, and autonomous agent orchestration. The library provides a structured framework for defining executable tools and enforcing JSON schemas, ensuring that model outputs remain programmatically compatible with downstream systems. The SDK distinguishes itself through its robust request orchestration and

Spring AI is an application framework for Java that provides a portable, fluent API for integrating AI models, tools, and vector stores into applications. It wraps multiple AI providers behind a common interface, allowing developers to switch between chat, embedding, image, and speech models without changing application code. The framework includes a chainable chat client API similar to WebClient or RestClient, supports both synchronous and streaming interactions, and offers structured output conversion that transforms unstructured AI responses into strongly-typed Java objects. The framework

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

The agent-framework is an LLM agent orchestration framework and multi-agent workflow engine designed for building autonomous AI agents. It provides a tool integration layer for binding external functions, APIs, and sandboxed code as executable tools for language models. The framework distinguishes itself through a graph-based system for designing sequential and parallel task flows, featuring state management and checkpointing for long-running processes. It implements comprehensive conversational state management and an observability suite that uses telemetry to trace execution flows and monit

Swarms 是一个多代理编排框架和自主代理工具包，旨在协调大语言模型代理。它作为一个用于管理代理关系的工作流引擎，提供了构建具有集成内存、工具调用能力和推理循环的自主代理的基础设施。 该框架的特色在于其多代理共识系统，利用投票、对抗性辩论和裁判代理来合成高质量的响应。它支持多种协作模式，包括导演-工作者层次结构、专家合成以及基于自然语言描述的自动化群体架构生成。 该系统涵盖了广泛的运营功能，包括通过领域特定语言进行基于图和顺序的工作流编排、针对不同模型提供商的统一接口，以及与 Model Context Protocol 的集成以实现动态工具发现。它还包括对检索增强生成、状态持久内存以及将代理功能公开为 Web 服务的能力的支持。 该项目提供用于代理管理的命令行界面，并支持通过 YAML 和模块化 markdown 技能文件进行配置。

Youtu Agent is an open-source framework for building, running, and evaluating autonomous agents powered by large language models. It provides the core infrastructure for creating agents that follow reasoning loops, use toolkits, and coordinate with other agents to solve complex tasks, all managed through YAML-driven configuration files. The framework distinguishes itself through its support for multi-agent orchestration, where a planner agent decomposes tasks and coordinates specialized worker agents, and through its integration with the Model Context Protocol for connecting to external toolk

AdalFlow 是一个自主 AI 代理框架和 LLM 应用库，旨在构建模块化工作流。它作为一个模型无关的接口和 RAG 流水线编排器，允许用户开发 ReAct 代理，利用迭代推理和外部工具执行来解决复杂任务。 该项目通过一个提示词优化系统脱颖而出，该系统使用文本梯度下降自动优化提示词模板和少样本示例。它将模型反馈视为可微分信号，实现了一种 LLM 反向传播形式，从而根据评估指标迭代提高输出质量。 该框架涵盖了广泛的功能面，包括带有语义向量搜索和重排序的检索增强生成、用于可观测性的基于跨度的执行追踪，以及模式驱动的结构化解析。它为众多专有和开源模型提供商提供了统一的通信层，并支持将 Python 函数转换为标准化的工具接口。 该系统使用 Python 实现，并与 MLflow 集成以进行工作流跟踪和分析。

Koog is an LLM agent framework used to build autonomous entities that execute tool-based workflows. It utilizes a graph-based workflow engine to define agent behaviors and decision paths as a directed graph of nodes and edges. The framework distinguishes itself through a model provider orchestrator that enables dynamic switching, load balancing, and automatic fallbacks between different AI backends. It implements the Model Context Protocol to connect agents to remote tool servers and features a RAG memory system using vector embeddings to maintain long-term conversation context. The project

This project provides a translation layer and set of adapters designed to bridge AI agents with the Model Context Protocol. It functions as an integration layer that allows agents to operate as protocol-compliant servers and enables the conversion of protocol-based tools into formats compatible with agent frameworks and logic graphs. The adapters facilitate tool interoperability by wrapping external protocol tools for use within agent workflows and exposing internal agent capabilities to any client implementing the Model Context Protocol. This creates a communication bridge that supports inte