A unified TypeScript/JavaScript package to use LLMs across ALL platforms with support for 17 major providers, streaming, MCP tools, and intelligent response parsing
Lightweight multi-LLM agent library for building CLI AI assistants
Universal MCP server for multi-LLM plan review
Multi-LLM Provider System for Cognition V3
🥇 Cheapest LLM router on RouterArena ($0.05/1K) · 15K+ downloads in 2 weeks · Open-source AI gateway with parallel multi-LLM execution across 47+ providers, ensemble voting, semantic cache, and budget enforcement
AI Coding Framework for Claude Code — 56 agents, 45 skills, multi-LLM orchestration
Multi-LLM failover with circuit breakers, cost tracking, and intelligent retry. Cloudflare Workers native.
Library to query multiple LLM providers in a consistent way
Multi-LLM Provider System for Claude Flow V3
Mahabali AI multi-LLM assistant CLI
A Node.js package for multi-LLM agent support
Multi-LLM code review pipeline — parallel reviewers, structured debate, consensus verdict
Driver-agnostic multi-LLM peer review for code decisions. Bring your own CLI; Chorus convenes 2-4 other LLMs to review the work before you ship.
Multi-LLM Provider System for Claude Flow V3
Drop-in AI chatbot SDK + React widget. Multi-LLM with fallback, business config, anti-hallucination guards. One import, one config — your site has a chatbot.
BMAD-BUFF: Revolutionary Multi-LLM Orchestration System for 10x Faster AI-Driven Development
Perplexity Sonar API adapter for Loop Engine multi-LLM steps (grounded search + reasoning).
Unified MCP server for multi-LLM consultation — registers tools from all available providers (Gemini, Codex, Ollama) behind runtime availability checks
Multi-LLM orchestration framework with agentic execution, memory/RAG, and training data generation
Multi-LLM Council Terminal Suite - Three-stage consensus with GPT, Gemini, and Claude
FastCode — a blazing-fast TUI coding assistant. Multi-LLM, skills.sh skills, slash commands. Works on Termux, Linux, Windows, and macOS.
BMAD-BUFF: Enhanced BMAD-METHOD™ with Multi-LLM Orchestration via BUFF Router and ROMA Orchestrator
MCP server for Agence — AI governance framework with policy enforcement, skills, memory, and multi-LLM consensus
Multi-LLM Development Server (Claude, Codex, Gemini) - A unified interface for AI coding assistants
Unified multi-provider LLM client with support for OpenAI, Anthropic, Ollama, and LMStudio
AI Agent SDK for Game NPCs
MCP server for multi-LLM peer review and council deliberation workflow
A command-line tool for interacting with LLMs
A fully self-contained AI agent backend framework with built-in web services, multi-LLM provider support, and comprehensive tool execution
CLI for consulting stronger LLMs from your agent workflow
A flexible few-shot intent classification library for natural language processing
Local orchestration layer for coordinating multiple LLM backends
CLI for skill-veil behavioral analysis
Core library for skill-veil behavioral analysis
MCP server that dispatches prompts to peer LLM CLIs (codex/gemini/minimax/claude) and returns verdict-parsed output.
CUDA Virtual Memory Management bindings for elastic KV cache allocation in Candle
Soka is a Ruby framework for building AI agents using the ReAct (Reasoning and Acting) pattern. It supports multiple AI providers including Gemini AI Studio, OpenAI, and Anthropic.
RobotLab is a Ruby framework for building and orchestrating multi-robot LLM workflows. Built on ruby_llm, it provides robots with template-based prompts, tools, and shared memory; networks for coordinating multiple robots with intelligent routing; MCP (Model Context Protocol) integration for external tool servers; and a memory system with Redis backend and semantic caching. Optional gems add Rails integration (robot_lab-rails), durable learning (robot_lab-durable), Ractor concurrency (robot_lab-ractor), and document storage (robot_lab-document_store).
A unified interface for multiple LLM providers (OpenAI, Anthropic, Google, OpenRouter). Supports streaming, tool calling, and configurable logging.
ace-sim executes preset-driven simulation chains across multiple providers so teams can validate ideas, review tasks, and compare synthesis outcomes before taking action.
RCrewAI is a powerful Ruby framework for creating autonomous AI agent crews that collaborate to solve complex tasks. Build intelligent workflows with reasoning agents, tool usage, memory systems, and human oversight. Key Features: • Multi-Agent Orchestration: Create crews of specialized AI agents that work together • Multi-LLM Support: OpenAI GPT-4, Anthropic Claude, Google Gemini, Azure OpenAI, Ollama • Rich Tool Ecosystem: Web search, file operations, SQL databases, email, code execution, PDF processing • Agent Memory: Short-term and long-term memory for learning from past executions • Human-in-the-Loop: Interactive approval workflows and collaborative decision making • Advanced Task Management: Dependencies, retries, async execution, and context sharing • Hierarchical Teams: Manager agents that coordinate and delegate to specialist agents • Production Ready: Security controls, error handling, comprehensive logging, and monitoring • Ruby-First Design: Built specifically for Ruby developers with idiomatic patterns • CLI Tools: Command-line interface for creating and managing AI crews
Ruby AI Agents SDK enables creating complex AI workflows with multi-agent orchestration, tool execution, safety guardrails, and provider-agnostic LLM integration.
Asynchronous LLM API requests via patient_http using prompt_builder for multi-format LLM API support.
RubyCoded is a terminal-based AI coding assistant built in Ruby. It provides a full TUI chat interface with support for multiple LLM providers (OpenAI, Anthropic, etc.), an agent mode with filesystem tools for reading, writing, and editing project files, a plan mode for structured task planning, and a plugin system for extensibility.
Pocketrb is a Ruby AI agent framework featuring async message bus architecture, multi-LLM support (Claude, OpenRouter, RubyLLM), multi-channel messaging (CLI, Telegram, WhatsApp), planning system, context compaction, and simple JSON-based memory with keyword matching.
Yorishiro is a CLI-based LLM agent that supports multiple providers (Anthropic, OpenAI, Ollama), built-in tools for file operations and command execution, MCP server integration, and plan mode.
Production-grade coding agent with tool execution, middleware pipeline, context compaction, session persistence, and multi-provider LLM support.
Ruby port of LangGraph - build stateful, multi-actor applications with LLMs using a graph-based workflow engine with Pregel execution model
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