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.
Building blocks for frontier OpenAI agents in Rust. Nanocodex empowers you with Codex-level performance anywhere.
🌋 Build AI agents that seamlessly combine LLM reasoning with real-world actions via MCP tools — in just a few lines of TypeScript.
Omnigent is an open-source AI agent framework and meta-harness: orchestrate Claude Code, Codex, Cursor, Pi, and custom agents — swap harnesses without rewriting, enforce policies and sandboxing, and collaborate in real time from any device.
Build and run agents you can see, understand and trust.
1flowbase: self-hosted AI gateway with protocol translation, dispatch, chat logs, built-in backend & React blocks to combine AI with business data. All managed by your Agent via MCP.
Go language library for reading and writing Microsoft Excel™ (XLAM / XLSM / XLSX / XLTM / XLTX) spreadsheets
Deterministic safety solutions for probabilistic AI agents
An Agentic Framework for Reflective PowerPoint Generation
Build autonomous AI agents in Python.
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
🔬 A Researcher&Agent-Friendly Framework for Time Series Analysis. Train Any Model on Any Dataset!
Connect AI agents across any network — zero config, encrypted, skill-based routing
Neo.mjs is a self-evolving software organism: a professional end-to-end AI engineering team whose cross-model swarm inhabits live apps via Neural Link, Active Hybrid GraphRAG, DreamService, and self-healing loops.
Open-source AI assistant ecosystem with MCP integrations, multimodal workflows, IoT support, and cross-platform voice interaction.
An event-driven framework designed to build and orchestrate multi-agent AI systems. It enables seamless integration of AI agents with real-world data sources and systems, facilitating complex, multi-step workflows.
SkillX: Automatically Constructing Skill Knowledge Bases for Agents
LLM agents as your hyperparameter optimizer.
Implementation of Podlite markup language
Java test automation framework for web, mobile, API, CLI, database, and desktop E2E testing with a fluent API and built-in reporting.
A lightweight, lightning-fast, in-process vector database
The Context Layer for unstructured data: typed, versioned datasets over S3, GCS, Azure
AI Agent Engineering Platform built on an Open Source TypeScript AI Agent Framework
Code, Build and Evaluate agents - excellent Model and Skills/MCP/ACP/A2A Support