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A developer tool for testing and debugging Model Context Protocol (MCP) servers. It allows users to test the compliance of their MCP servers with the latest MCP specs, supports various transports like STDIO, SSE, and Streamable HTTP, features an LLM Playground for testing server behavior against different models, provides comprehensive logging and error reporting for MCP server development, and offers a modern developer experience with multiple server connections and saved configurations. The tool is built using Next.js and integrates MCP capabilities, AI SDKs from OpenAI, Anthropic, and Ollama, and various technologies like Node.js, TypeScript, and Next.js.

Conduit is an open-source, cross-platform mobile application for Open-WebUI, providing a native mobile experience for interacting with your self-hosted AI infrastructure. It supports real-time chat, model selection, conversation management, markdown rendering, theme support, voice input, file uploads, multi-modal support, secure storage, folder management, and tools invocation. Conduit offers multiple authentication flows and follows a clean architecture pattern with Riverpod for state management, Dio for HTTP networking, WebSocket for real-time streaming, and Flutter Secure Storage for credential management.

Automodel is a Python library for automating the process of building and evaluating machine learning models. It provides a set of tools and utilities to streamline the model development workflow, from data preprocessing to model selection and evaluation. With Automodel, users can easily experiment with different algorithms, hyperparameters, and feature engineering techniques to find the best model for their dataset. The library is designed to be user-friendly and customizable, allowing users to define their own pipelines and workflows. Automodel is suitable for data scientists, machine learning engineers, and anyone looking to quickly build and test machine learning models without the need for manual intervention.

LLM4S provides a simple, robust, and scalable framework for building Large Language Models (LLM) applications in Scala. It aims to leverage Scala's type safety, functional programming, JVM ecosystem, concurrency, and performance advantages to create reliable and maintainable AI-powered applications. The framework supports multi-provider integration, execution environments, error handling, Model Context Protocol (MCP) support, agent frameworks, multimodal generation, and Retrieval-Augmented Generation (RAG) workflows. It also offers observability features like detailed trace logging, monitoring, and analytics for debugging and performance insights.

Community plugins repository for Google Firebase Genkit, containing various plugins for AI APIs and Vector Stores. Developed by The Fire Company, this repository offers plugins like genkitx-anthropic, genkitx-cohere, genkitx-groq, genkitx-mistral, genkitx-openai, genkitx-convex, and genkitx-hnsw. Users can easily install and use these plugins in their projects, with examples provided in the documentation. The repository also showcases products like Fireview and Giftit built using these plugins, and welcomes contributions from the community.

AIGNE DocSmith is a powerful AI-driven documentation generation tool that automates the creation of detailed, structured, and multi-language documentation directly from source code. It intelligently analyzes codebase to generate a comprehensive document structure, populates content with high-quality AI-powered generation, supports seamless translation into 12+ languages, integrates with AIGNE Hub for large language models, offers Discuss Kit publishing, automatically updates documentation with source code changes, and allows for individual document optimization.

AgentNeo is an advanced, open-source Agentic AI Application Observability, Monitoring, and Evaluation Framework designed to provide deep insights into AI agents, Large Language Model (LLM) calls, and tool interactions. It offers robust logging, visualization, and evaluation capabilities to help debug and optimize AI applications with ease. With features like tracing LLM calls, monitoring agents and tools, tracking interactions, detailed metrics collection, flexible data storage, simple instrumentation, interactive dashboard, project management, execution graph visualization, and evaluation tools, AgentNeo empowers users to build efficient, cost-effective, and high-quality AI-driven solutions.

Buster is a modern analytics platform designed with AI in mind, focusing on self-serve experiences powered by Large Language Models. It addresses pain points in existing tools by advocating for AI-centric app development, cost-effective data warehousing, improved CI/CD processes, and empowering data teams to create powerful, user-friendly data experiences. The platform aims to revolutionize AI analytics by enabling data teams to build deep integrations and own their entire analytics stack.

Aegra is a self-hosted AI agent backend platform that provides LangGraph power without vendor lock-in. Built with FastAPI + PostgreSQL, it offers complete control over agent orchestration for teams looking to escape vendor lock-in, meet data sovereignty requirements, enable custom deployments, and optimize costs. Aegra is Agent Protocol compliant and perfect for teams seeking a free, self-hosted alternative to LangGraph Platform with zero lock-in, full control, and compatibility with existing LangGraph Client SDK.

RSTGameTranslation is a tool designed for translating game text into multiple languages efficiently. It provides a user-friendly interface for game developers to easily manage and localize their game content. With RSTGameTranslation, developers can streamline the translation process, ensuring consistency and accuracy across different language versions of their games. The tool supports various file formats commonly used in game development, making it versatile and adaptable to different project requirements. Whether you are working on a small indie game or a large-scale production, RSTGameTranslation can help you reach a global audience by making localization a seamless and hassle-free experience.

Shimmy is a 5.1MB single-binary local inference server providing OpenAI-compatible endpoints for GGUF models. It offers fast, reliable AI inference with sub-second responses, zero configuration, and automatic port management. Perfect for developers seeking privacy, cost-effectiveness, speed, and easy integration with popular tools like VSCode and Cursor. Shimmy is designed to be invisible infrastructure that simplifies local AI development and deployment.

evi-run is a powerful, production-ready multi-agent AI system built on Python using the OpenAI Agents SDK. It offers instant deployment, ultimate flexibility, built-in analytics, Telegram integration, and scalable architecture. The system features memory management, knowledge integration, task scheduling, multi-agent orchestration, custom agent creation, deep research, web intelligence, document processing, image generation, DEX analytics, and Solana token swap. It supports flexible usage modes like private, free, and pay mode, with upcoming features including NSFW mode, task scheduler, and automatic limit orders. The technology stack includes Python 3.11, OpenAI Agents SDK, Telegram Bot API, PostgreSQL, Redis, and Docker & Docker Compose for deployment.

QFurina is a powerful and easily extensible Python QQ robot backend service that provides a range of automation and interactive features. It supports multiple messaging platforms and has a robust plugin system, allowing users to easily expand and customize functionality.

ChatGPT WebUI is a user-friendly web graphical interface for various LLMs like ChatGPT, providing simplified features such as core ChatGPT conversation and document retrieval dialogues. It has been optimized for better RAG retrieval accuracy and supports various search engines. Users can deploy local language models easily and interact with different LLMs like GPT-4, Azure OpenAI, and more. The tool offers powerful functionalities like GPT4 API configuration, system prompt setup for role-playing, and basic conversation features. It also provides a history of conversations, customization options, and a seamless user experience with themes, dark mode, and PWA installation support.

Claude Code Agents is an open-source AI agent system designed to enhance development workflows by providing specialized AI agents for orchestration, resilience engineering, and organizational memory. These agents offer specialized expertise across technologies, AI system with organizational memory, and an agent orchestration system. The system includes features such as engineering excellence by design, advanced orchestration system, Task Master integration, live MCP integrations, professional-grade workflows, and organizational intelligence. It is suitable for solo developers, small teams, enterprise teams, and open-source projects. The system requires a one-time bootstrap setup for each project to analyze the tech stack, select optimal agents, create configuration files, set up Task Master integration, and validate system readiness.

Handit.ai is an autonomous engineer tool designed to fix AI failures 24/7. It catches failures, writes fixes, tests them, and ships PRs automatically. It monitors AI applications, detects issues, generates fixes, tests them against real data, and ships them as pull requests—all automatically. Users can write JavaScript, TypeScript, Python, and more, and the tool automates what used to require manual debugging and firefighting.

A developer tool for testing and debugging Model Context Protocol (MCP) servers. It allows users to test the compliance of their MCP servers with the latest MCP specs, supports various transports like STDIO, SSE, and Streamable HTTP, features an LLM Playground for testing server behavior against different models, provides comprehensive logging and error reporting for MCP server development, and offers a modern developer experience with multiple server connections and saved configurations. The tool is built using Next.js and integrates MCP capabilities, AI SDKs from OpenAI, Anthropic, and Ollama, and various technologies like Node.js, TypeScript, and Next.js.

TermNet is an AI-powered terminal assistant that connects a Large Language Model (LLM) with shell command execution, browser search, and dynamically loaded tools. It streams responses in real-time, executes tools one at a time, and maintains conversational memory across steps. The project features terminal integration for safe shell command execution, dynamic tool loading without code changes, browser automation powered by Playwright, WebSocket architecture for real-time communication, a memory system to track planning and actions, streaming LLM output integration, a safety layer to block dangerous commands, dual interface options, a notification system, and scratchpad memory for persistent note-taking. The architecture includes a multi-server setup with servers for WebSocket, browser automation, notifications, and web UI. The project structure consists of core backend files, various tools like web browsing and notification management, and servers for browser automation and notifications. Installation requires Python 3.9+, Ollama, and Chromium, with setup steps provided in the README. The tool can be used via the launcher for managing components or directly by starting individual servers. Additional tools can be added by registering them in `toolregistry.json` and implementing them in Python modules. Safety notes highlight the blocking of dangerous commands, allowed risky commands with warnings, and the importance of monitoring tool execution and setting appropriate timeouts.

The Google Generative AI SDK for Dart enables developers to utilize cutting-edge Large Language Models (LLMs) for creating language applications. It provides access to the Gemini API for generating content using state-of-the-art models. Developers can integrate the SDK into their Dart or Flutter applications to leverage powerful AI capabilities. It is recommended to use the SDK for server-side API calls to ensure the security of API keys and protect against potential key exposure in mobile or web apps.

This repository contains an assistant proposal for the Semantic Kernel, allowing the usage of assistants without relying on OpenAI Assistant APIs. It runs locally planners and plugins for the assistants, providing scenarios like Assistant with Semantic Kernel plugins, Multi-Assistant conversation, and AutoGen conversation. The Semantic Kernel is a lightweight SDK enabling integration of AI Large Language Models with conventional programming languages, offering functions like semantic functions, native functions, and embeddings-based memory. Users can bring their own model for the assistants and host them locally. The repository includes installation instructions, usage examples, and information on creating new conversation threads with the assistant.

ezlocalai is an artificial intelligence server that simplifies running multimodal AI models locally. It handles model downloading and server configuration based on hardware specs. It offers OpenAI Style endpoints for integration, voice cloning, text-to-speech, voice-to-text, and offline image generation. Users can modify environment variables for customization. Supports NVIDIA GPU and CPU setups. Provides demo UI and workflow visualization for easy usage.

llmproxy is a reverse proxy for LLM API based on Cloudflare Worker, supporting platforms like OpenAI, Gemini, and Groq. The interface is compatible with the OpenAI API specification and can be directly accessed using the OpenAI SDK. It provides a convenient way to interact with various AI platforms through a unified API endpoint, enabling seamless integration and usage in different applications.

This repository contains a simple Python Flask App utilizing the Google AI Gemini API to explore multi-modal capabilities. It provides a basic UI and Flask backend for easy integration and testing. The app allows users to interact with the AI model through chat messages, making it a great starting point for developers interested in AI-powered applications.

KaibanJS is a JavaScript-native framework for building multi-agent AI systems. It enables users to create specialized AI agents with distinct roles and goals, manage tasks, and coordinate teams efficiently. The framework supports role-based agent design, tool integration, multiple LLMs support, robust state management, observability and monitoring features, and a real-time agentic Kanban board for visualizing AI workflows. KaibanJS aims to empower JavaScript developers with a user-friendly AI framework tailored for the JavaScript ecosystem, bridging the gap in the AI race for non-Python developers.

Sweep is an AI junior developer that turns bugs and feature requests into code changes. It automatically handles developer experience improvements like adding type hints and improving test coverage.

The Teams AI Library is a software development kit (SDK) that helps developers create bots that can interact with Teams and Microsoft 365 applications. It is built on top of the Bot Framework SDK and simplifies the process of developing bots that interact with Teams' artificial intelligence capabilities. The SDK is available for JavaScript/TypeScript, .NET, and Python.

This guide is dedicated to Large Language Models (LLMs) that you can run on your home computer. It assumes your PC is a lower-end, non-gaming setup.

Supercharge WordPress Content Workflows and Engagement with Artificial Intelligence. Tap into leading cloud-based services like OpenAI, Microsoft Azure AI, Google Gemini and IBM Watson to augment your WordPress-powered websites. Publish content faster while improving SEO performance and increasing audience engagement. ClassifAI integrates Artificial Intelligence and Machine Learning technologies to lighten your workload and eliminate tedious tasks, giving you more time to create original content that matters.

Chatbot UI is an open-source AI chat app that allows users to create and deploy their own AI chatbots. It is easy to use and can be customized to fit any need. Chatbot UI is perfect for businesses, developers, and anyone who wants to create a chatbot.

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

uAgents is a Python library developed by Fetch.ai that allows for the creation of autonomous AI agents. These agents can perform various tasks on a schedule or take action on various events. uAgents are easy to create and manage, and they are connected to a fast-growing network of other uAgents. They are also secure, with cryptographically secured messages and wallets.

Griptape is a modular Python framework for building AI-powered applications that securely connect to your enterprise data and APIs. It offers developers the ability to maintain control and flexibility at every step. Griptape's core components include Structures (Agents, Pipelines, and Workflows), Tasks, Tools, Memory (Conversation Memory, Task Memory, and Meta Memory), Drivers (Prompt and Embedding Drivers, Vector Store Drivers, Image Generation Drivers, Image Query Drivers, SQL Drivers, Web Scraper Drivers, and Conversation Memory Drivers), Engines (Query Engines, Extraction Engines, Summary Engines, Image Generation Engines, and Image Query Engines), and additional components (Rulesets, Loaders, Artifacts, Chunkers, and Tokenizers). Griptape enables developers to create AI-powered applications with ease and efficiency.