MCP Context Forge is a powerful tool for generating context-aware data for machine learning models. It provides functionalities to create diverse datasets with contextual information, enhancing the performance of AI algorithms. The tool supports various data formats and allows users to customize the context generation process easily. With MCP Context Forge, users can efficiently prepare training data for tasks requiring contextual understanding, such as sentiment analysis, recommendation systems, and natural language processing.

oh-my-pi is an AI coding agent for the terminal, providing tools for interactive coding, AI-powered git commits, Python code execution, LSP integration, time-traveling streamed rules, interactive code review, task management, interactive questioning, custom TypeScript slash commands, universal config discovery, MCP & plugin system, web search & fetch, SSH tool, Cursor provider integration, multi-credential support, image generation, TUI overhaul, edit fuzzy matching, and more. It offers a modern terminal interface with smart session management, supports multiple AI providers, and includes various tools for coding, task management, code review, and interactive questioning.

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.

Tokscale is a high-performance CLI tool and visualization dashboard for tracking token usage and costs across multiple AI coding agents. It helps monitor and analyze token consumption from various AI coding tools, providing real-time pricing calculations using LiteLLM's pricing data. Inspired by the Kardashev scale, Tokscale measures token consumption as users scale the ranks of AI-augmented development. It offers interactive TUI mode, multi-platform support, real-time pricing, detailed breakdowns, web visualization, flexible filtering, and social platform features.

9Router is a free AI router tool designed to help developers maximize their AI subscriptions, auto-route to free and cheap AI models with smart fallback, and avoid hitting limits and wasting money. It offers features like real-time quota tracking, format translation between OpenAI, Claude, and Gemini, multi-account support, auto token refresh, custom model combinations, request logging, cloud sync, usage analytics, and flexible deployment options. The tool supports various providers like Claude Code, Codex, Gemini CLI, GitHub Copilot, GLM, MiniMax, iFlow, Qwen, and Kiro, and allows users to create combos for different scenarios. Users can connect to the tool via CLI tools like Cursor, Claude Code, Codex, OpenClaw, and Cline, and deploy it on VPS, Docker, or Cloudflare Workers.

AI Real Estate Assistant is a modern platform that uses AI to assist real estate agencies in helping buyers and renters find their ideal properties. It features multiple AI model providers, intelligent query processing, advanced search and retrieval capabilities, and enhanced user experience. The tool is built with a FastAPI backend and Next.js frontend, offering semantic search, hybrid agent routing, and real-time analytics.

ONNX Runtime Server is a server that provides TCP and HTTP/HTTPS REST APIs for ONNX inference. It aims to offer simple, high-performance ML inference and a good developer experience. Users can provide inference APIs for ONNX models without writing additional code by placing the models in the directory structure. Each session can choose between CPU or CUDA, analyze input/output, and provide Swagger API documentation for easy testing. Ready-to-run Docker images are available, making it convenient to deploy the server.

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.

LlamaFarm is a comprehensive AI framework that empowers users to build powerful AI applications locally, with full control over costs and deployment options. It provides modular components for RAG systems, vector databases, model management, prompt engineering, and fine-tuning. Users can create differentiated AI products without needing extensive ML expertise, using simple CLI commands and YAML configs. The framework supports local-first development, production-ready components, strategy-based configuration, and deployment anywhere from laptops to the cloud.

Claude Code Bridge (ccb) is a new multi-model collaboration tool that enables effective collaboration among multiple AI models in a split-pane CLI environment. It offers features like visual and controllable interface, persistent context maintenance, token savings, and native workflow integration. The tool allows users to unleash the full power of CLI by avoiding model bias, cognitive blind spots, and context limitations. It provides a new WYSIWYG solution for multi-model collaboration, making it easier to control and visualize multiple AI models simultaneously.

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.

A Model Context Protocol (MCP) server that provides AI assistants with comprehensive access to shadcn/ui v4 components, blocks, demos, and metadata. It allows users to seamlessly retrieve React, Svelte, Vue, and React Native implementations for AI-powered development workflows. The server supports multi-frameworks, component source code, demos, blocks, metadata access, directory browsing, smart caching, SSE transport, and Docker containerization. Users can quickly start the server, integrate with Claude Desktop, deploy with SSE transport or Docker, and access documentation for installation, configuration, integration, usage, frameworks, troubleshooting, and API reference. The server supports React, Svelte, Vue, and React Native implementations, with options for UI library selection. It enables AI-powered development, multi-client deployments, production environments, component discovery, multi-framework learning, rapid prototyping, and code generation.

README-AI is a developer tool that auto-generates README.md files using a combination of data extraction and generative AI. It streamlines documentation creation and maintenance, enhancing developer productivity. This project aims to enable all skill levels, across all domains, to better understand, use, and contribute to open-source software. It offers flexible README generation, supports multiple large language models (LLMs), provides customizable output options, works with various programming languages and project types, and includes an offline mode for generating boilerplate README files without external API calls.

ProxyPilot is a powerful local API proxy tool built in Go that eliminates the need for separate API keys when using Claude Code, Codex, Gemini, Kiro, and Qwen subscriptions with any AI coding tool. It handles OAuth authentication, token management, and API translation automatically, providing a single server to route requests. The tool supports multiple authentication providers, universal API translation, tool calling repair, extended thinking models, OAuth integration, multi-account support, quota auto-switching, usage statistics tracking, context compression, agentic harness for coding agents, session memory, system tray app, auto-updates, rollback support, and over 60 management APIs. ProxyPilot also includes caching layers for response and prompt caching to reduce latency and token usage.

Flyte 2 SDK is a pure Python tool for type-safe, distributed orchestration of agents, ML pipelines, and more. It allows users to write data pipelines, ML training jobs, and distributed compute in Python without any DSL constraints. With features like async-first parallelism and fine-grained observability, Flyte 2 offers a seamless workflow experience. Users can leverage core concepts like TaskEnvironments for container configuration, pure Python workflows for flexibility, and async parallelism for distributed execution. Advanced features include sub-task observability with tracing and remote task execution. The tool also provides native Jupyter integration for running and monitoring workflows directly from notebooks. Configuration and deployment are made easy with configuration files and commands for deploying and running workflows. Flyte 2 is licensed under the Apache 2.0 License.

General Bots is a self-hosted AI automation platform and LLM conversational platform focused on convention over configuration and code-less approaches. It serves as the core API server handling LLM orchestration, business logic, database operations, and multi-channel communication. The platform offers features like multi-vendor LLM API, MCP + LLM Tools Generation, Semantic Caching, Web Automation Engine, Enterprise Data Connectors, and Git-like Version Control. It enforces a ZERO TOLERANCE POLICY for code quality and security, with strict guidelines for error handling, performance optimization, and code patterns. The project structure includes modules for core functionalities like Rhai BASIC interpreter, security, shared types, tasks, auto task system, file operations, learning system, and LLM assistance.

The 'nlp-llms-resources' repository is a comprehensive resource list for Natural Language Processing (NLP) and Large Language Models (LLMs). It covers a wide range of topics including traditional NLP datasets, data acquisition, libraries for NLP, neural networks, sentiment analysis, optical character recognition, information extraction, semantics, topic modeling, multilingual NLP, domain-specific LLMs, vector databases, ethics, costing, books, courses, surveys, aggregators, newsletters, papers, conferences, and societies. The repository provides valuable information and resources for individuals interested in NLP and LLMs.

AData is a free and open-source A-share database that focuses on transaction-related data. It provides comprehensive data on stocks, including basic information, market data, and sentiment analysis. AData is designed to be easy to use and integrate with other applications, making it a valuable tool for quantitative trading and AI training.

PIXIU is a project designed to support the development, fine-tuning, and evaluation of Large Language Models (LLMs) in the financial domain. It includes components like FinBen, a Financial Language Understanding and Prediction Evaluation Benchmark, FIT, a Financial Instruction Dataset, and FinMA, a Financial Large Language Model. The project provides open resources, multi-task and multi-modal financial data, and diverse financial tasks for training and evaluation. It aims to encourage open research and transparency in the financial NLP field.

Hezar is an all-in-one AI library designed specifically for the Persian community. It brings together various AI models and tools, making it easy to use AI with just a few lines of code. The library seamlessly integrates with Hugging Face Hub, offering a developer-friendly interface and task-based model interface. In addition to models, Hezar provides tools like word embeddings, tokenizers, feature extractors, and more. It also includes supplementary ML tools for deployment, benchmarking, and optimization.

Text Embeddings Inference (TEI) is a toolkit for deploying and serving open source text embeddings and sequence classification models. TEI enables high-performance extraction for popular models like FlagEmbedding, Ember, GTE, and E5. It implements features such as no model graph compilation step, Metal support for local execution on Macs, small docker images with fast boot times, token-based dynamic batching, optimized transformers code for inference using Flash Attention, Candle, and cuBLASLt, Safetensors weight loading, and production-ready features like distributed tracing with Open Telemetry and Prometheus metrics.

CodeProject.AI Server is a standalone, self-hosted, fast, free, and open-source Artificial Intelligence microserver designed for any platform and language. It can be installed locally without the need for off-device or out-of-network data transfer, providing an easy-to-use solution for developers interested in AI programming. The server includes a HTTP REST API server, backend analysis services, and the source code, enabling users to perform various AI tasks locally without relying on external services or cloud computing. Current capabilities include object detection, face detection, scene recognition, sentiment analysis, and more, with ongoing feature expansions planned. The project aims to promote AI development, simplify AI implementation, focus on core use-cases, and leverage the expertise of the developer community.

Spark NLP is a state-of-the-art Natural Language Processing library built on top of Apache Spark. It provides simple, performant, and accurate NLP annotations for machine learning pipelines that scale easily in a distributed environment. Spark NLP comes with 36000+ pretrained pipelines and models in more than 200+ languages. It offers tasks such as Tokenization, Word Segmentation, Part-of-Speech Tagging, Named Entity Recognition, Dependency Parsing, Spell Checking, Text Classification, Sentiment Analysis, Token Classification, Machine Translation, Summarization, Question Answering, Table Question Answering, Text Generation, Image Classification, Image to Text (captioning), Automatic Speech Recognition, Zero-Shot Learning, and many more NLP tasks. Spark NLP is the only open-source NLP library in production that offers state-of-the-art transformers such as BERT, CamemBERT, ALBERT, ELECTRA, XLNet, DistilBERT, RoBERTa, DeBERTa, XLM-RoBERTa, Longformer, ELMO, Universal Sentence Encoder, Llama-2, M2M100, BART, Instructor, E5, Google T5, MarianMT, OpenAI GPT2, Vision Transformers (ViT), OpenAI Whisper, and many more not only to Python and R, but also to JVM ecosystem (Java, Scala, and Kotlin) at scale by extending Apache Spark natively.

Scikit-LLM is a tool that seamlessly integrates powerful language models like ChatGPT into scikit-learn for enhanced text analysis tasks. It allows users to leverage large language models for various text analysis applications within the familiar scikit-learn framework. The tool simplifies the process of incorporating advanced language processing capabilities into machine learning pipelines, enabling users to benefit from the latest advancements in natural language processing.

Weave is a toolkit for developing Generative AI applications, built by Weights & Biases. With Weave, you can log and debug language model inputs, outputs, and traces; build rigorous, apples-to-apples evaluations for language model use cases; and organize all the information generated across the LLM workflow, from experimentation to evaluations to production. Weave aims to bring rigor, best-practices, and composability to the inherently experimental process of developing Generative AI software, without introducing cognitive overhead.

LLMStack is a no-code platform for building generative AI agents, workflows, and chatbots. It allows users to connect their own data, internal tools, and GPT-powered models without any coding experience. LLMStack can be deployed to the cloud or on-premise and can be accessed via HTTP API or triggered from Slack or Discord.

The VisionCraft API is a free API for using over 100 different AI models. From images to sound.

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.

PyRIT is an open access automation framework designed to empower security professionals and ML engineers to red team foundation models and their applications. It automates AI Red Teaming tasks to allow operators to focus on more complicated and time-consuming tasks and can also identify security harms such as misuse (e.g., malware generation, jailbreaking), and privacy harms (e.g., identity theft). The goal is to allow researchers to have a baseline of how well their model and entire inference pipeline is doing against different harm categories and to be able to compare that baseline to future iterations of their model. This allows them to have empirical data on how well their model is doing today, and detect any degradation of performance based on future improvements.

Tabby is a self-hosted AI coding assistant, offering an open-source and on-premises alternative to GitHub Copilot. It boasts several key features: * Self-contained, with no need for a DBMS or cloud service. * OpenAPI interface, easy to integrate with existing infrastructure (e.g Cloud IDE). * Supports consumer-grade GPUs.

SPEAR (Simulator for Photorealistic Embodied AI Research) is a powerful tool for training embodied agents. It features 300 unique virtual indoor environments with 2,566 unique rooms and 17,234 unique objects that can be manipulated individually. Each environment is designed by a professional artist and features detailed geometry, photorealistic materials, and a unique floor plan and object layout. SPEAR is implemented as Unreal Engine assets and provides an OpenAI Gym interface for interacting with the environments via Python.

Magick is a groundbreaking visual AIDE (Artificial Intelligence Development Environment) for no-code data pipelines and multimodal agents. Magick can connect to other services and comes with nodes and templates well-suited for intelligent agents, chatbots, complex reasoning systems and realistic characters.