Popular GitHub Repositories for Service Discovery Protocol

Dify is an open-source LLM app development platform. Dify's intuitive interface combines AI workflow, RAG pipeline, agent capabilities, model management, observability features and more, letting you quickly go from prototype to production.

? Papers & tech blogs by companies sharing their work on data science & machine learning in production.

An open protocol enabling communication and interoperability between opaque agentic applications.

The Cloud-Native API Gateway and AI Gateway

State-of-the-Art Deep Learning scripts organized by models - easy to train and deploy with reproducible accuracy and performance on enterprise-grade infrastructure.

? Scalable embedding, reasoning, ranking for images and sentences with CLIP

ModelScope: bring the notion of Model-as-a-Service to life.

The easiest way to serve AI apps and models - Build Model Inference APIs, Job queues, LLM apps, Multi-model pipelines, and more!

The most reliable AI agent framework that supports MCP.

Venom is a high-performance system developed with JavaScript to create a bot for WhatsApp, support for creating any interaction, such as customer service, media sending, sentence recognition based on artificial intelligence and all types of design architecture for WhatsApp.

Firebase SDK for Apple App Development

Democratizing Deep-Learning for Drug Discovery, Quantum Chemistry, Materials Science and Biology

Build effective agents using Model Context Protocol and simple workflow patterns

Install, run and deploy your own decentralized AI agent service

Context aware, pluggable and customizable data protection and de-identification SDK for text and images

Standardized Serverless ML Inference Platform on Kubernetes

5ire is a cross-platform desktop AI assistant, MCP client. It compatible with major service providers, supports local knowledge base and tools via model context protocol servers .

Full toolkit for running an AI agent service built with LangGraph, FastAPI and Streamlit

Control GenAI interactions with power, precision, and consistency using LLM-native Conversation Design paradigms

Python Library for learning (Structure and Parameter), inference (Probabilistic and Causal), and simulations in Bayesian Networks.