Open-source LLM router & AI cost optimizer. Routes simple prompts to cheap/local models, complex ones to premium — automatically. Drop-in OpenAI-compatible proxy for Claude Code, Codex, Cursor, OpenClaw. Saves 40-70% on AI API costs. Self-hosted, no middleman.

Route every prompt to the best LLM — for you specifically.

A prompt-aware LLM router that predicts which models can complete each request, then selects the cheapest capable one: 53.2% lower cost and +1.9 pts completion on our tested dataset.

Reduce your LLM costs by 40-70% automatically. Routes prompts locally, compacts context, tracks real savings.

Local, zero-token intent routing for chat, tooling, coding, and planning prompts.

Host-aware model routing for coding agents. Python library + MCP server for Claude Code, Codex, Gemini CLI, Copilot, Cursor, and Aider.

Blazing-fast, zero-cost local LLM router. Classify and route prompts to specialized AI models with <1ms latency using heuristic rules.

22-agent Mixture-of-Agents pipeline with LongLoop for 24h autonomous iteration: smart routing sends easy tasks to Flash, hard tasks to flagships, cutting token costs ~90%. One-command deploy（一键部署，22 个 agent 的 MoA 流水线，长程循环可自主迭代 24 小时，智能路由省约 90% token 成本）

Intelligent multi-model LLM routing gateway — route each request to the optimal model, save 40-70% on API costs. Single binary, OpenAI-compatible.

Route prompts to local large language models instantly to cut costs and reduce latency with smart, zero-overhead classification under 1 millisecond.

Energy-efficient AI prompt routing system — sends simple prompts to lightweight models and reserves larger models for complex reasoning to cut compute, latency, and energy.

Run a team of AI coding agents (Claude Code, Codex, Gemini, Hermes) side by side in tmux, with a YAML-defined ACL. Zero dependencies.

The control plane for Claude Code. Run a dozen MCP servers and a hundred skills. Pay context for only the ones doing work right now.

Local prompt routing studio for structured AI workflows and execution handoff.

Intelligent LLM router that dynamically routes prompts between local Ollama (Qwen) and cloud models (Gemini) using complexity scoring, semantic caching, and cost-aware decisioning.

面向 Agent 的多层传统八字分析 Skills 与主题路由

Intelligent LLM request router for Azure OpenAI — automatically routes prompts to GPT-4o-mini or GPT-4o based on complexity, task type, environment, and budget. Cuts AI API costs by 60-80% with zero impact on application quality.

OpenAI-compatible LLM gateway that routes each prompt to the cheapest qualified model — local Ollama first, cloud only when needed.

ML system that routes LLM prompts to the cheapest capable model tier using XGBoost and DistilBERT+LoRA, trained on 51k LMSYS Chatbot Arena samples to cut inference costs by 40–50%.

MCP server that intelligently routes prompts across Claude, Gemini, and GPT-4o based on task type — minimising token cost without sacrificing quality.