This repository, 'awesome-mcp-servers-devops', is a curated list of Model Context Protocol servers for DevOps workflows. It includes servers for various aspects of DevOps such as infrastructure, CI/CD, monitoring, security, and cloud operations. The repository provides information on different MCP servers available for tools like GitHub, GitLab, Azure DevOps, Gitea, Terraform, Vault, Pulumi, Kubernetes, Docker Hub, Portainer, Qovery, various command line and local operation tools, browser automation tools, code execution tools, coding agents, aggregators, CI/CD tools like Argo CD, Jenkins, GitHub Actions, Codemagic, DevOps visibility tools, build tools, cloud platforms like AWS, Azure, Cloudflare, Alibaba Cloud, observability tools like Grafana, Datadog, Prometheus, VictoriaMetrics, Alertmanager, APM & monitoring tools, security tools like Snyk, Semgrep, and community security servers, collaboration tools like Atlassian, Jira, project management tools, service desks, Notion, and more.

AIdea Server is an open-source Golang-based server that integrates mainstream large language models and drawing models. It supports various functionalities including OpenAI's GPT-3.5 and GPT-4, Anthropic's Claude instant and Claude 2.1, Google's Gemini Pro, as well as Chinese models like Tongyi Qianwen, Wenxin Yiyuan, and more. It also supports open-source large models like Yi 34B, Llama2, and AquilaChat 7B. Additionally, it provides features for text-to-image, super-resolution, coloring black and white images, generating art fonts and QR codes, among others.

Cyber is a superintelligence protocol that aims to create a decentralized and censorship-resistant internet. It uses a novel consensus mechanism called CometBFT and a knowledge graph to store and process information. Cyber is designed to be scalable, secure, and efficient, and it has the potential to revolutionize the way we interact with the internet.

AgentKit Samples is a repository containing a series of examples and tutorials to help users understand, implement, and integrate various functionalities of AgentKit into their applications. The platform offers a complete solution for building, deploying, and maintaining AI agents, significantly reducing the complexity of developing intelligent applications. The repository provides different levels of examples and tutorials, including basic tutorials for understanding AgentKit's concepts and use cases, as well as more complex examples for experienced developers.

Web Builder is a low-code front-end framework based on Material for Angular, offering a rich component library for excellent digital innovation experience. It allows rapid construction of modern responsive UI, multi-theme, multi-language web pages through drag-and-drop visual configuration. The framework includes a beautiful admin theme, complete front-end solutions, and AI integration in the Pro version for optimizing copy, creating components, and generating pages with a single sentence.

VoiceBench is a repository containing code and data for benchmarking LLM-Based Voice Assistants. It includes a leaderboard with rankings of various voice assistant models based on different evaluation metrics. The repository provides setup instructions, datasets, evaluation procedures, and a curated list of awesome voice assistants. Users can submit new voice assistant results through the issue tracker for updates on the ranking list.

This repository provides a detailed tutorial on how to build your own large language model (LLM) from scratch. It includes all the code necessary to create a GPT-like LLM, covering the encoding, pre-training, and fine-tuning processes. The tutorial is written in a clear and concise style, with plenty of examples and illustrations to help you understand the concepts involved. It is suitable for developers and researchers with some programming experience who are interested in learning more about LLMs and how to build them.

Awesome-LLMs-for-Video-Understanding is a repository dedicated to exploring Video Understanding with Large Language Models. It provides a comprehensive survey of the field, covering models, pretraining, instruction tuning, and hybrid methods. The repository also includes information on tasks, datasets, and benchmarks related to video understanding. Contributors are encouraged to add new papers, projects, and materials to enhance the repository.

LLamaTuner is a repository for the Efficient Finetuning of Quantized LLMs project, focusing on building and sharing instruction-following Chinese baichuan-7b/LLaMA/Pythia/GLM model tuning methods. The project enables training on a single Nvidia RTX-2080TI and RTX-3090 for multi-round chatbot training. It utilizes bitsandbytes for quantization and is integrated with Huggingface's PEFT and transformers libraries. The repository supports various models, training approaches, and datasets for supervised fine-tuning, LoRA, QLoRA, and more. It also provides tools for data preprocessing and offers models in the Hugging Face model hub for inference and finetuning. The project is licensed under Apache 2.0 and acknowledges contributions from various open-source contributors.

Llama Stack defines and standardizes core building blocks for AI application development, providing a unified API layer, plugin architecture, prepackaged distributions, developer interfaces, and standalone applications. It offers flexibility in infrastructure choice, consistent experience with unified APIs, and a robust ecosystem with integrated distribution partners. The tool simplifies building, testing, and deploying AI applications with various APIs and environments, supporting local development, on-premises, cloud, and mobile deployments.

Jiwu Chat Tauri APP is a desktop chat application based on Nuxt3 + Tauri + Element Plus framework. It provides a beautiful user interface with integrated chat and social functions. It also supports AI shopping chat and global dark mode. Users can engage in real-time chat, share updates, and interact with AI customer service through this application.

AstrBot is a powerful and versatile tool that leverages the capabilities of large language models (LLMs) like GPT-3, GPT-3.5, and GPT-4 to enhance communication and automate tasks. It seamlessly integrates with popular messaging platforms such as QQ, QQ Channel, and Telegram, enabling users to harness the power of AI within their daily conversations and workflows.

This repository is a collection of resources focused on interpretability in large language models (LLMs). It aims to help beginners get started in the area and keep researchers updated on the latest progress. It includes libraries, blogs, tutorials, forums, tools, programs, papers, and more related to interpretability in LLMs.

DataFlow is a data preparation and training system designed to parse, generate, process, and evaluate high-quality data from noisy sources, improving the performance of large language models in specific domains. It constructs diverse operators and pipelines, validated to enhance domain-oriented LLM's performance in fields like healthcare, finance, and law. DataFlow also features an intelligent DataFlow-agent capable of dynamically assembling new pipelines by recombining existing operators on demand.

Hello-Agents is a comprehensive tutorial on building intelligent agent systems, covering both theoretical foundations and practical applications. The tutorial aims to guide users in understanding and building AI-native agents, diving deep into core principles, architectures, and paradigms of intelligent agents. Users will learn to develop their own multi-agent applications from scratch, gaining hands-on experience with popular low-code platforms and agent frameworks. The tutorial also covers advanced topics such as memory systems, context engineering, communication protocols, and model training. By the end of the tutorial, users will have the skills to develop real-world projects like intelligent travel assistants and cyber towns.

Nx is a build system optimized for monorepos, featuring AI-powered architectural awareness and advanced CI capabilities. It provides faster task scheduling, caching, and more for existing workspaces. Nx Cloud enhances CI by offering remote caching, task distribution, automated e2e test splitting, and task flakiness detection. The tool aims to scale monorepos efficiently and improve developer productivity.

The Cheat-Sheet Collection for DevOps, Engineers, IT professionals, and more is a curated list of cheat sheets for various tools and technologies commonly used in the software development and IT industry. It includes cheat sheets for Nginx, Docker, Ansible, Python, Go (Golang), Git, Regular Expressions (Regex), PowerShell, VIM, Jenkins, CI/CD, Kubernetes, Linux, Redis, Slack, Puppet, Google Cloud Developer, AI, Neural Networks, Machine Learning, Deep Learning & Data Science, PostgreSQL, Ajax, AWS, Infrastructure as Code (IaC), System Design, and Cyber Security.

The mcp-fundamentals repository is a collection of fundamental concepts and examples related to microservices, cloud computing, and DevOps. It covers topics such as containerization, orchestration, CI/CD pipelines, and infrastructure as code. The repository provides hands-on exercises and code samples to help users understand and apply these concepts in real-world scenarios. Whether you are a beginner looking to learn the basics or an experienced professional seeking to refresh your knowledge, mcp-fundamentals has something for everyone.

This repository, 'awesome-mcp-servers-devops', is a curated list of Model Context Protocol servers for DevOps workflows. It includes servers for various aspects of DevOps such as infrastructure, CI/CD, monitoring, security, and cloud operations. The repository provides information on different MCP servers available for tools like GitHub, GitLab, Azure DevOps, Gitea, Terraform, Vault, Pulumi, Kubernetes, Docker Hub, Portainer, Qovery, various command line and local operation tools, browser automation tools, code execution tools, coding agents, aggregators, CI/CD tools like Argo CD, Jenkins, GitHub Actions, Codemagic, DevOps visibility tools, build tools, cloud platforms like AWS, Azure, Cloudflare, Alibaba Cloud, observability tools like Grafana, Datadog, Prometheus, VictoriaMetrics, Alertmanager, APM & monitoring tools, security tools like Snyk, Semgrep, and community security servers, collaboration tools like Atlassian, Jira, project management tools, service desks, Notion, and more.

This repository contains a collection of sample applications and Jupyter Notebooks for hands-on experience with Pinecone vector databases and common AI patterns, tools, and algorithms. It includes production-ready examples for review and support, as well as learning-optimized examples for exploring AI techniques and building applications. Users can contribute, provide feedback, and collaborate to improve the resource.

OpenAGI is an AI agent creation package designed for researchers and developers to create intelligent agents using advanced machine learning techniques. The package provides tools and resources for building and training AI models, enabling users to develop sophisticated AI applications. With a focus on collaboration and community engagement, OpenAGI aims to facilitate the integration of AI technologies into various domains, fostering innovation and knowledge sharing among experts and enthusiasts.

Sirji is an agentic AI framework for software development where various AI agents collaborate via a messaging protocol to solve software problems. It uses standard or user-generated recipes to list tasks and tips for problem-solving. Agents in Sirji are modular AI components that perform specific tasks based on custom pseudo code. The framework is currently implemented as a Visual Studio Code extension, providing an interactive chat interface for problem submission and feedback. Sirji sets up local or remote development environments by installing dependencies and executing generated code.

Dewhale is a GitHub-Powered AI tool designed for effortless development. It utilizes prompt engineering techniques under the GPT-4 model to issue commands, allowing users to generate code with lower usage costs and easy customization. The tool seamlessly integrates with GitHub, providing version control, code review, and collaborative features. Users can join discussions on the design philosophy of Dewhale and explore detailed instructions and examples for setting up and using the tool.

The Modular Accelerated Xecution (MAX) platform is an integrated suite of AI libraries, tools, and technologies that unifies commonly fragmented AI deployment workflows. MAX accelerates time to market for the latest innovations by giving AI developers a single toolchain that unlocks full programmability, unparalleled performance, and seamless hardware portability.

This repository, 'awesome-mcp-servers-devops', is a curated list of Model Context Protocol servers for DevOps workflows. It includes servers for various aspects of DevOps such as infrastructure, CI/CD, monitoring, security, and cloud operations. The repository provides information on different MCP servers available for tools like GitHub, GitLab, Azure DevOps, Gitea, Terraform, Vault, Pulumi, Kubernetes, Docker Hub, Portainer, Qovery, various command line and local operation tools, browser automation tools, code execution tools, coding agents, aggregators, CI/CD tools like Argo CD, Jenkins, GitHub Actions, Codemagic, DevOps visibility tools, build tools, cloud platforms like AWS, Azure, Cloudflare, Alibaba Cloud, observability tools like Grafana, Datadog, Prometheus, VictoriaMetrics, Alertmanager, APM & monitoring tools, security tools like Snyk, Semgrep, and community security servers, collaboration tools like Atlassian, Jira, project management tools, service desks, Notion, and more.

CB-Tumblebug (CB-TB) is a system for managing multi-cloud infrastructure consisting of resources from multiple cloud service providers. It provides an overview, features, and architecture. The tool supports various cloud providers and resource types, with ongoing development and localization efforts. Users can deploy a multi-cloud infra with GPUs, enjoy multiple LLMs in parallel, and utilize LLM-related scripts. The tool requires Linux, Docker, Docker Compose, and Golang for building the source. Users can run CB-TB with Docker Compose or from the Makefile, set up prerequisites, contribute to the project, and view a list of contributors. The tool is licensed under an open-source license.

Robusta is a tool designed to enhance Prometheus notifications for Kubernetes environments. It offers features such as smart grouping to reduce notification spam, AI investigation for alert analysis, alert enrichment with additional data like pod logs, self-healing capabilities for defining auto-remediation rules, advanced routing options, problem detection without PromQL, change-tracking for Kubernetes resources, auto-resolve functionality, and integration with various external systems like Slack, Teams, and Jira. Users can utilize Robusta with or without Prometheus, and it can be installed alongside existing Prometheus setups or as part of an all-in-one Kubernetes observability stack.

AI+CloudOps is a cloud-native operations management platform designed for enterprises. It aims to integrate artificial intelligence technology with cloud-native practices to significantly improve the efficiency and level of operations work. The platform offers features such as AIOps for monitoring data analysis and alerts, multi-dimensional permission management, visual CMDB for resource management, efficient ticketing system, deep integration with Prometheus for real-time monitoring, and unified Kubernetes management for cluster optimization.

Kaito is an operator that automates the AI/ML inference model deployment in a Kubernetes cluster. It manages large model files using container images, avoids tuning deployment parameters to fit GPU hardware by providing preset configurations, auto-provisions GPU nodes based on model requirements, and hosts large model images in the public Microsoft Container Registry (MCR) if the license allows. Using Kaito, the workflow of onboarding large AI inference models in Kubernetes is largely simplified.

This repository contains assets related to AI/ML workloads on Google Kubernetes Engine (GKE). Run optimized AI/ML workloads with Google Kubernetes Engine (GKE) platform orchestration capabilities. A robust AI/ML platform considers the following layers: Infrastructure orchestration that support GPUs and TPUs for training and serving workloads at scale Flexible integration with distributed computing and data processing frameworks Support for multiple teams on the same infrastructure to maximize utilization of resources

TiDB is an open-source distributed SQL database that supports Hybrid Transactional and Analytical Processing (HTAP) workloads. It is MySQL compatible and features horizontal scalability, strong consistency, and high availability.

Nvidia GPU exporter for prometheus, using `nvidia-smi` binary to gather metrics.