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Microsoft Copilot Studio agent build automation with Claude Code

Multi-agent orchestration system with 18 specialized agents for AI workflows. Built-in integrations with Openclaw and LangChain.

On-chain credit scoring and soulbound identity for autonomous agents

CoralBricks + LangChain integration: retriever, chat history, memory helper, and agent tools.

Universal payment infrastructure for AI Agents - Support multiple payment providers with unified API

Browser automation CLI for AI agents - minimal token cost (~68 tokens)

BrowseCraft core library - browser automation for AI agents

Self-regulating autonomous AI work orchestrator — dispatches LLM agent waves, manages budget headroom, runs cross-model quality review

A terminal-based AI agent that decomposes projects into epics, user stories, tasks, and sprint plans.

Classified Agent CLI — Synthesis Hackathon ($75K Prizes). Build + submit AI agents in 60s. PyVax-powered Web3 scaffolding.

Hugging Face Space: AI_GameScene_3D_Asset_Splitting_Tool

MiMo-V2-Omni is a frontier omni-modal model that natively processes image, video, and audio inputs within a unified architecture. It combines strong multimodal perception with agentic capability - visual grounding, multi-step planning, tool use, and code execution - making it well-suited for complex real-world tasks that span modalities. 256K context window.

MiMo-V2-Pro is Xiaomi's flagship foundation model, featuring over 1T total parameters and a 1M context length, deeply optimized for agentic scenarios. It is highly adaptable to general agent frameworks like OpenClaw. It ranks among the global top tier in the standard PinchBench and ClawBench benchmarks, with perceived performance approaching that of Opus 4.6. MiMo-V2-Pro is designed to serve as the brain of agent systems, orchestrating complex workflows, driving production engineering tasks, and

MiniMax-M2.7 is a next-generation large language model designed for autonomous, real-world productivity and continuous improvement. Built to actively participate in its own evolution, M2.7 integrates advanced agentic capabilities through multi-agent collaboration, enabling it to plan, execute, and refine complex tasks across dynamic environments. Trained for production-grade performance, M2.7 handles workflows such as live debugging, root cause analysis, financial modeling, and full document ge

NVIDIA Nemotron 3 Super is a 120B-parameter open hybrid MoE model, activating just 12B parameters for maximum compute efficiency and accuracy in complex multi-agent applications. Built on a hybrid Mamba-Transformer Mixture-of-Experts architecture with multi-token prediction (MTP), it delivers over 50% higher token generation compared to leading open models. The model features a 1M token context window for long-term agent coherence, cross-document reasoning, and multi-step task planning. Latent

LangChain/LangGraph middleware for building AI agents with memory, skills, and filesystem support

CamouChat: Anti-detection WhatsApp automation SDK with end-to-end encrypted storage, async SQLite/PostgreSQL, per-profile sandboxing, and human-like browser behaviour

LLM observability SDK — track token usage, tool calls, and conversations via Pentatonic TES

Testing framework for multi-agent LLM systems

Scaffold hexagonal architecture Python projects with AI-agent-ready patterns