Awesome GitHub RepositoriesAgent Versioning

This platform serves as a centralized management system for organizing, refining, and versioning AI instructions and agent skills. It functions as a repository that enables users to store, categorize, and retrieve structured prompts, ensuring consistent performance across various artificial intelligence models. By integrating with the Model Context Protocol, the system allows external AI assistants and development environments to discover and access these instruction libraries directly. The platform distinguishes itself through its focus on prompt engineering and automated refinement, utilizi

Multica is an autonomous coding agent manager and LLM agent orchestration platform. It coordinates teams of autonomous agents to execute coding tasks and manage their lifecycles through a centralized dashboard. The system provides multi-tenant agent workspaces that isolate agents, settings, and project issues into distinct organizational boundaries. The platform distinguishes itself through an agent skill library that captures successful task solutions as reusable, versioned skills. These skills are shared across the agent team and pinned using content hashes to ensure consistent behavior acr

Deepagents is an LLM agent orchestration platform and stateful application server designed for deploying and managing AI agents built with computational graphs. It provides a containerized runtime environment that handles agent execution, state persistence, and the versioning of AI assistants. The platform distinguishes itself through deep integration with the Model Context Protocol, allowing agents to function as servers that expose tools and capabilities to external clients. It features a sophisticated observability suite for capturing execution traces, performing LLM-based evaluations agai

Mastra is an orchestration framework designed for building, deploying, and managing autonomous AI agents and multi-agent systems. It provides a comprehensive suite of primitives for creating resilient AI applications, including durable workflow orchestration, event-driven agent loops, and semantic memory management. By integrating these core components, the platform enables developers to build complex, multi-step processes that can reason about goals and execute tasks without manual intervention. The framework distinguishes itself through its focus on observability and secure, isolated execut

Letta is a framework for building, deploying, and managing autonomous AI agents that maintain persistent state across long-term interactions. It provides a comprehensive suite of primitives for defining agents with configurable personas, modular memory blocks, and tool-use capabilities, enabling them to retain user preferences and conversation history over extended sessions. The platform distinguishes itself through its advanced memory management and orchestration capabilities. It allows agents to autonomously update their own memory, perform retrieval-augmented generation, and coordinate com

Lark CLI is a terminal-based tool designed for automating tasks and managing resources across the Lark and Feishu productivity ecosystem. It functions as a cloud workspace automator and REST API client, providing a command line interface to programmatically manage organizational documents, calendars, emails, and tasks. The project distinguishes itself through an AI agent skill framework that allows for the integration and deployment of both bundled and custom skills. It features an identity-aware execution context that enables switching between user and bot identities, and employs a sidecar-b

Llama-stack 是一个标准化的编排栈和生成式 AI API 网关。它提供了一个统一的通信层和一致的接口，用于部署、管理和与各种大语言模型提供商及部署进行交互。 该系统充当代理（agent）框架，管理工具执行和版本化的技能包，以自动化复杂任务。它包括一个批处理系统，用于通过离线处理处理大量异步请求，以及一个用于存储和搜索文档以实现检索增强生成（RAG）的向量数据库接口。 该栈涵盖了高级功能，包括 AI 代理编排、模型部署以及模型 API 的标准化，从而允许在不重写应用程序代码的情况下切换提供商。

OpenSkills is an agent capability orchestrator and skill manager designed to sync, version, and distribute standardized skill definitions across autonomous agent environments. It functions as a system for installing domain-specific instruction sets and specialized knowledge into large language model agents, acting as a context injector to load task-oriented prompts and technical documentation into an agent's active operational window. The project distinguishes itself through a git-based distribution framework, allowing agent capabilities to be fetched and updated from remote version control s

Higress is an AI API gateway and cloud-native traffic manager that functions as a Kubernetes ingress controller. It provides a centralized system for routing, securing, and optimizing traffic directed toward large language models, AI agents, and microservice architectures. The project distinguishes itself through deep AI orchestration, including the ability to host and manage Model Context Protocol servers that transform REST APIs into tools for AI agents. It features specialized AI infrastructure for model request proxying, protocol translation across multiple providers, and semantic-based c

mistral.rs is an inference engine for large language models that runs locally and exposes models behind OpenAI and Anthropic-compatible APIs. It serves as a multi-model serving platform, capable of loading several models in a single server process with per-request routing and on-demand loading and unloading. The engine supports multimodal inference, processing text alongside images, video, audio, and speech inputs, and includes a quantized model deployment runtime that reduces memory use and speeds up inference on consumer hardware. The project distinguishes itself through an agentic tool exe

Skills is a command-line tool for managing reusable instruction sets, called skills, that configure the behavior of AI coding agents. It provides a versioned registry of agent prompts that can be discovered, installed, updated, and removed through a CLI interface, with skills stored as declarative configuration files injected directly into a project's file system. The tool supports the full lifecycle of agent skill management, including searching a public registry by keyword, browsing a leaderboard of community-contributed skills, inspecting remote repositories before installation, and genera

DLSS Swapper is a desktop tool that manages and replaces upscaling DLLs in game directories, supporting DLSS, FSR, and XeSS technologies. It identifies DLL versions by computing file hashes and matching them against a known database, then swaps the files directly in the game folder without modifying executables or memory. The tool automatically detects installed games across Steam, GOG, Epic Games, Ubisoft Connect, Xbox App, and Battle.net, and also supports manual addition of games by specifying the executable path. It maintains a local repository of multiple upscaling DLL versions, allowing

DiskLruCache is a disk-backed key-value cache library for Android and Java environments that stores data on the filesystem within a configurable byte limit. It uses a least-recently-used (LRU) eviction policy to automatically remove old entries when the cache exceeds its allocated size, and maintains a journal file to reconstruct its in-memory state after a process restart. The cache provides atomic write operations that first write new data to a temporary file before atomically renaming it, preventing partial or corrupted reads during concurrent access. It returns frozen snapshots of cache e

MemOS is an open-source persistent memory layer for AI agents and large language models, providing a self-hosted server that stores and retrieves structured memory across sessions. It enables AI systems to recall user preferences, history, and context without retraining, using a graph-based API and a web management interface for viewing, editing, and organizing memory items, skills, traces, and knowledge bases. The system distinguishes itself through a portable memory interchange protocol that allows memory to be transferred between different AI models, devices, and applications, along with a

AIOS is an LLM agent operating system and orchestration kernel designed to manage memory, resource scheduling, and tool execution for multiple autonomous AI agents. It serves as a comprehensive framework for developing and deploying agents, featuring a dedicated resource manager that coordinates model backends, GPU memory, and isolated kernel instances. The system distinguishes itself through a semantic memory engine that uses vector search and autonomous clustering for long-term knowledge management, and a semantic file system that allows users to control computer files and system operations

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