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.

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

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

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.

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.

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.

CLI-first OpenAI-compatible LLM router/proxy for coding agents that picks the cheapest fast-enough model and proves speed, savings, and prompt-free privacy.

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

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

Prompt posture router for coding tasks; pairs with causetrace

Route prompts between local and cloud LLMs based on task complexity. Use local models (Ollama) for simple tasks, cloud APIs for complex ones. Save 80%+ on AI costs.

Analyze MCP tool schema overhead, token usage, and per-turn cost for AI agents. Estimate context bloat, tool-calling overhead, and routing savings for OpenAI-compatible backends.

Direct requests to the correct host using automated routing for coding agents.