ATLAS (Adaptive Task & Logic Automation System) is a high-performance Model Context Protocol server designed for LLMs to manage complex task hierarchies. Built with TypeScript, it features ACID-compliant storage, efficient task tracking, and intelligent template management. ATLAS provides LLM Agents task management through a clean, flexible tool interface. The server implements the Model Context Protocol (MCP) for standardized communication between LLMs and external systems, offering hierarchical task organization, task state management, smart templates, enterprise features, and performance optimization.

PaperBanana is an automated academic illustration tool designed for AI scientists. It implements an agentic framework for generating publication-quality academic diagrams and statistical plots from text descriptions. The tool utilizes a two-phase multi-agent pipeline with iterative refinement, Gemini-based VLM planning, and image generation. It offers a CLI, Python API, and MCP server for IDE integration, along with Claude Code skills for generating diagrams, plots, and evaluating diagrams. PaperBanana is not affiliated with or endorsed by the original authors or Google Research, and it may differ from the original system described in the paper.

Autohand Code CLI is an autonomous coding agent in CLI form that uses the ReAct pattern to understand, plan, and execute code changes. It is designed for seamless coding experience without context switching or copy-pasting. The tool is fast, intuitive, and extensible with modular skills. It can be used to automate coding tasks, enforce code quality, and speed up development. Autohand can be integrated into team workflows and CI/CD pipelines to enhance productivity and efficiency.

Dexto is a lightweight runtime for creating and running AI agents that turn natural language into real-world actions. It serves as the missing intelligence layer for building AI applications, standalone chatbots, or as the reasoning engine inside larger products. Dexto features a powerful CLI and Web UI for running AI agents, supports multiple interfaces, allows hot-swapping of LLMs from various providers, connects to remote tool servers via the Model Context Protocol, is config-driven with version-controlled YAML, offers production-ready core features, extensibility for custom services, and enables multi-agent collaboration via MCP and A2A.

Augustus is a Go-based LLM vulnerability scanner designed for security professionals to test large language models against a wide range of adversarial attacks. It integrates with 28 LLM providers, covers 210+ adversarial attacks including prompt injection, jailbreaks, encoding exploits, and data extraction, and produces actionable vulnerability reports. The tool is built for production security testing with features like concurrent scanning, rate limiting, retry logic, and timeout handling out of the box.

FDABench is a benchmark tool designed for evaluating data agents' reasoning ability over heterogeneous data in analytical scenarios. It offers 2,007 tasks across various data sources, domains, difficulty levels, and task types. The tool provides ready-to-use data agent implementations, a DAG-based evaluation system, and a framework for agent-expert collaboration in dataset generation. Key features include data agent implementations, comprehensive evaluation metrics, multi-database support, different task types, extensible framework for custom agent integration, and cost tracking. Users can set up the environment using Python 3.10+ on Linux, macOS, or Windows. FDABench can be installed with a one-command setup or manually. The tool supports API configuration for LLM access and offers quick start guides for database download, dataset loading, and running examples. It also includes features like dataset generation using the PUDDING framework, custom agent integration, evaluation metrics like accuracy and rubric score, and a directory structure for easy navigation.

GPT-Load is a high-performance, enterprise-grade AI API transparent proxy service designed for enterprises and developers needing to integrate multiple AI services. Built with Go, it features intelligent key management, load balancing, and comprehensive monitoring capabilities for high-concurrency production environments. The tool serves as a transparent proxy service, preserving native API formats of various AI service providers like OpenAI, Google Gemini, and Anthropic Claude. It supports dynamic configuration, distributed leader-follower deployment, and a Vue 3-based web management interface. GPT-Load is production-ready with features like dual authentication, graceful shutdown, and error recovery.

Docutranslate is a versatile tool for translating documents efficiently. It supports multiple file formats and languages, making it ideal for businesses and individuals needing quick and accurate translations. The tool uses advanced algorithms to ensure high-quality translations while maintaining the original document's formatting. With its user-friendly interface, Docutranslate simplifies the translation process and saves time for users. Whether you need to translate legal documents, technical manuals, or personal letters, Docutranslate is the go-to solution for all your document translation needs.

RepairAgent is an autonomous LLM-based agent for automated program repair targeting the Defects4J benchmark. It uses an LLM-driven loop to localize, analyze, and fix Java bugs. The tool requires Docker, VS Code with Dev Containers extension, OpenAI API key, disk space of ~40 GB, and internet access. Users can get started with RepairAgent using either VS Code Dev Container or Docker Image. Running RepairAgent involves checking out the buggy project version, autonomous bug analysis, fix candidate generation, and testing against the project's test suite. Users can configure hyperparameters for budget control, repetition handling, commands limit, and external fix strategy. The tool provides output structure, experiment overview, individual analysis scripts, and data on fixed bugs from the Defects4J dataset.

MCP DevTools is a high-performance server written in Go that replaces multiple Node.js and Python-based servers. It provides access to essential developer tools through a unified, modular interface. The server is efficient, with minimal memory footprint and fast response times. It offers a comprehensive tool suite for agentic coding, including 20+ essential developer agent tools. The tool registry allows for easy addition of new tools. The server supports multiple transport modes, including STDIO, HTTP, and SSE. It includes a security framework for multi-layered protection and a plugin system for adding new tools.

Ruler is a tool designed to centralize AI coding assistant instructions, providing a single source of truth for managing instructions across multiple AI coding tools. It helps in avoiding inconsistent guidance, duplicated effort, context drift, onboarding friction, and complex project structures by automatically distributing instructions to the right configuration files. With support for nested rule loading, Ruler can handle complex project structures with context-specific instructions for different components. It offers features like centralised rule management, nested rule loading, automatic distribution, targeted agent configuration, MCP server propagation, .gitignore automation, and a simple CLI for easy configuration management.

Dingo is a data quality evaluation tool that automatically detects data quality issues in datasets. It provides built-in rules and model evaluation methods, supports text and multimodal datasets, and offers local CLI and SDK usage. Dingo is designed for easy integration into evaluation platforms like OpenCompass.

AgentOps is a toolkit for evaluating and developing robust and reliable AI agents. It provides benchmarks, observability, and replay analytics to help developers build better agents. AgentOps is open beta and can be signed up for here. Key features of AgentOps include: - Session replays in 3 lines of code: Initialize the AgentOps client and automatically get analytics on every LLM call. - Time travel debugging: (coming soon!) - Agent Arena: (coming soon!) - Callback handlers: AgentOps works seamlessly with applications built using Langchain and LlamaIndex.

PDFMathTranslate is a tool designed for translating scientific papers and conducting bilingual comparisons. It preserves formulas, charts, table of contents, and annotations. The tool supports multiple languages and diverse translation services. It provides a command-line tool, interactive user interface, and Docker deployment. Users can try the application through online demos. The tool offers various installation methods including command-line, portable, graphic user interface, and Docker. Advanced options allow users to customize translation settings. Additionally, the tool supports secondary development through APIs for Python and HTTP. Future plans include parsing layout with DocLayNet based models, fixing page rotation and format issues, supporting non-PDF/A files, and integrating plugins for Zotero and Obsidian.

Shodh-Memory is a cognitive memory system designed for AI agents to persist memory across sessions, learn from experience, and run entirely offline. It features Hebbian learning, activation decay, and semantic consolidation, packed into a single ~17MB binary. Users can deploy it on cloud, edge devices, or air-gapped systems to enhance the memory capabilities of AI agents.

A TypeScript toolkit for building AI-driven video workflows on the server, powered by Mux! @mux/ai provides purpose-driven workflow functions and primitive functions that integrate with popular AI/LLM providers like OpenAI, Anthropic, and Google. It offers pre-built workflows for tasks like generating summaries and tags, content moderation, chapter generation, and more. The toolkit is cost-effective, supports multi-modal analysis, tone control, and configurable thresholds, and provides full TypeScript support. Users can easily configure credentials for Mux and AI providers, as well as cloud infrastructure like AWS S3 for certain workflows. @mux/ai is production-ready, offers composable building blocks, and supports universal language detection.

ATLAS (Adaptive Task & Logic Automation System) is a high-performance Model Context Protocol server designed for LLMs to manage complex task hierarchies. Built with TypeScript, it features ACID-compliant storage, efficient task tracking, and intelligent template management. ATLAS provides LLM Agents task management through a clean, flexible tool interface. The server implements the Model Context Protocol (MCP) for standardized communication between LLMs and external systems, offering hierarchical task organization, task state management, smart templates, enterprise features, and performance optimization.

The Scale AI Python SDK is a tool that provides a Python interface for interacting with the Scale API. It allows users to easily create tasks, manage projects, upload files, and work with evaluation tasks, training tasks, and Studio assignments. The SDK handles error handling and provides detailed documentation for each method. Users can also manage teammates, project groups, and batches within the Scale Studio environment. The SDK supports various functionalities such as creating tasks, retrieving tasks, canceling tasks, auditing tasks, updating task attributes, managing files, managing team members, and working with evaluation and training tasks.

Backlog.md is a Markdown-native Task Manager & Kanban visualizer for any Git repository. It turns any folder with a Git repo into a self-contained project board powered by plain Markdown files and a zero-config CLI. Features include managing tasks as plain .md files, private & offline usage, instant terminal Kanban visualization, board export, modern web interface, AI-ready CLI, rich query commands, cross-platform support, and MIT-licensed open-source. Users can create tasks, view board, assign tasks to AI, manage documentation, make decisions, and configure settings easily.

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.

Tracecat is an open-source automation platform for security teams. It's designed to be simple but powerful, with a focus on AI features and a practitioner-obsessed UI/UX. Tracecat can be used to automate a variety of tasks, including phishing email investigation, evidence collection, and remediation plan generation.

OpenInference is a set of conventions and plugins that complement OpenTelemetry to enable tracing of AI applications. It provides a way to capture and analyze the performance and behavior of AI models, including their interactions with other components of the application. OpenInference is designed to be language-agnostic and can be used with any OpenTelemetry-compatible backend. It includes a set of instrumentations for popular machine learning SDKs and frameworks, making it easy to add tracing to your AI applications.

BricksLLM is a cloud native AI gateway written in Go. Currently, it provides native support for OpenAI, Anthropic, Azure OpenAI and vLLM. BricksLLM aims to provide enterprise level infrastructure that can power any LLM production use cases. Here are some use cases for BricksLLM: * Set LLM usage limits for users on different pricing tiers * Track LLM usage on a per user and per organization basis * Block or redact requests containing PIIs * Improve LLM reliability with failovers, retries and caching * Distribute API keys with rate limits and cost limits for internal development/production use cases * Distribute API keys with rate limits and cost limits for students

Kong, or Kong API Gateway, is a cloud-native, platform-agnostic, scalable API Gateway distinguished for its high performance and extensibility via plugins. It also provides advanced AI capabilities with multi-LLM support. By providing functionality for proxying, routing, load balancing, health checking, authentication (and more), Kong serves as the central layer for orchestrating microservices or conventional API traffic with ease. Kong runs natively on Kubernetes thanks to its official Kubernetes Ingress Controller.