🌐Web Agent Protocol (WAP) - Record and replay user interactions in the browser with MCP support

Next-gen AI memory layer with importance scoring, temporal decay, hierarchical memory, and YMYL prioritization

Qt C++ library for working with AI/LLM Providers and MCP

[ICML 2026] Meta Context Engineering via Agentic Skill Evolution

Python toolkit, MCP server, and agent skills for reproducible, auditable clickstream and event log analytics. Helps AI agents, data scientists and analysts build, validate, and cross-check product analytics, quantitative UX, customer journeys, graph-based user flows, behavioral segmentation, A/B tests, process mining models, Markov chain simulation

The AI Operating System for Delphi. 100% native framework with RAG 2.0, autonomous agents, MCP protocol, and universal LLM connector. Supports OpenAI, Claude, Gemini, Ollama, and more. Delphi 10.4+ (limited), full support from Delphi 12 Athens.

🔬 A Researcher&Agent-Friendly Framework for Time Series Analysis. Train Any Model on Any Dataset!

Umbrella package for SciTeX — reproducible science from raw data to manuscript

Connect AI agents across any network — zero config, encrypted, skill-based routing

Deploy production-ready AI services in minutes. One YAML file for agents, RAG pipelines, and MCP servers — run anywhere. Inspired by docker-compose.

A chatbot implementation compatible with MCP (terminal / streamlit supported)

Multi-agent research automation framework for LLM agents, with adversarial lab meetings, paper-review rounds, auditable Markdown workflows, an autonomous runtime watchdog, and a pixel-art web dashboard.

A modular Python framework implementing the Model Context Protocol (MCP). It features a standardized client-server architecture over StdIO, integrating LLMs with external tools, real-time weather data fetching, and an advanced RAG (Retrieval-Augmented Generation) system.

A framework for discovering, compiling, and validating reusable skills for scientific agents.

Solid Tumor Associative Modeling in Pathology

Config-driven engine that turns JSON into production-grade AI agents. Multi-agent orchestration, 12+ LLM providers, MCP/A2A protocols, RAG, persistent memory, and enterprise compliance (EU AI Act, GDPR, HIPAA). Built on Quarkus.

AgentStack is a production-grade multi-agent framework built on Mastra, delivering 50+ enterprise tools, 25+ specialized agents, and A2A/MCP orchestration for scalable AI systems. Focuses on financial intelligence, RAG pipelines, observability, and secure governance. ACP Openclaw, Gemini CLI, Opencode

Pixelize the real world on-chain

A Python wrapper for the Chemistry Development Kit (CDK)