Quick Verdict: Yes, You Need This

Here’s the short version: CCR is a local proxy layer for AI agents. You define routing rules in a single YAML file — “simple coding tasks go to my local Ollama, complex architecture work hits Claude Sonnet, code review passes through GPT-4o” — and every agent you run respects those rules. It works with Claude Code, Codex, OpenCode, Cursor CLI, and a growing list of backends.

The good: Zero cloud dependency, simple config, live health monitoring dashboard, cost-control rules per-task. The catch: You need Node.js 18+, and provider setup still requires API keys. But that’s it. Everything runs on your machine.

What Is Claude Code Router, Exactly?

CCR is an agent API gateway — think of it like a reverse proxy for your AI agents. Instead of each agent managing its own connection to Anthropic, OpenAI, or a local Ollama instance, they all route through CCR. The router handles:

• Model routing — pick the best provider per task based on complexity, cost, or latency
• Provider health checking — auto-detects dead endpoints and fails over
• Cost control — set per-task and per-session spending caps
• Unified logging — every agent request in one place

Plus, Kimi (Moonshot AI) sponsors this project, which means active development and regular releases. Last commit was yesterday — this is not abandonware.

CCR Core Features That Actually Matter

Model-Based Routing

This is the killer feature. You define routing rules with priority levels, and CCR evaluates each incoming agent request against them. My test config had three providers:

{
  "routing": {
    "rules": [
      {
        "name": "simple-tasks-to-local",
        "match": { "complexity": "low" },
        "route": { "provider": "ollama", "model": "llama3" },
        "priority": 10
      },
      {
        "name": "complex-tasks-to-advanced",
        "match": { "complexity": "high" },
        "route": { "provider": "claude-code", "model": "claude-sonnet-4" },
        "priority": 20
      }
    ]
  }
}

Still, low-complexity tasks hit my local Ollama (free, fast). Hard problems route to Claude Sonnet (smart, costs money). You never think about where a request is going — CCR decides based on the rules you set.

Health Monitoring Dashboard

Start the router, and a real-time dashboard launches at localhost:3456. I hit the health endpoint during testing and got back structured JSON with per-provider status:

{
  "overall": "degraded",
  "providers": {
    "codewhisperer-primary": false,
    "shuaihong-openai": true
  },
  "healthy": 1,
  "total": 2,
  "timestamp": "2026-07-15T00:21:32.051Z"
}

But one of my configured providers was down. So CCR flagged it immediately. That kind of transparency is rare in the agent tooling space — most tools either silently fail or swallow the error.

Per-Task Cost Controls

Set a max cost per task and per session. If an agent tries to route through a $0.10-per-call model when you capped it at $0.05, CCR blocks it and falls back to the next available provider. And this alone is worth installing it for — I’ve accidentally racked up API bills because an agent looped through GPT-4o on a simple search task.

Pro tip: Run CCR on a cheap cloud VPS instead of your local machine and you get 24/7 routing with a fixed monthly cost — no surprise bills. Vultr offers a $100 trial credit for new accounts, which covers months of lightweight agent routing. (affiliate link)

Quick Start: From Zero to Routing in 60 Seconds

I tested this on a Ryzen 9 Windows machine with Node.js 24. Here’s exactly what I did:

# Install globally — took about 9 seconds
npm install -g claude-code-router

# Check the version
ccr --version
# Output: 2.0.0

# Start the router
ccr start --port 3456

# Check provider health in another terminal
ccr health

The full install took under 30 seconds including the npm global install. Config file goes in ~/.claude-code-router/config-router.json. The router starts in the foreground — run it in a terminal tab or wrap it in a systemd service for persistent routing on a VPS.

If you want CCR running 24/7 for your development workflow, deploying it to a VPS is the simplest approach. DigitalOcean gives new users $200 in credit to experiment with — plenty to run CCR plus your other agent infrastructure for months. I’ve been using DO for all my self-hosted agent services and the uptime has been rock solid.

Real Scenario: Multi-Agent Routing in Practice

I had Claude Code running in one terminal and OpenCode in another. Here’s what I wanted: simple file-editing tasks (rename, refactor, lint) go to my local Ollama running Llama 3 for speed, but complex architecture discussions route to Claude Sonnet 4 for quality.

So I set up CCR with exactly those rules. Then I launched Claude Code through CCR:

ccr code

OpenCode through the same router. Both agents hit the same control plane. So when I asked Claude Code to refactor a React component (a medium-complexity task), CCR checked the rules, determined it didn’t match “complexity: high,” and routed it to Ollama. The response came back in about 12 seconds — free, local, no API call.

But when I asked OpenCode to design a database migration strategy, CCR matched “complexity: high,” routed to Claude Sonnet 4, and I got a detailed architecture plan.

Now what surprised me? The routing was transparent. I didn’t see any of this happening — the agents Just Worked. I only noticed when I checked the CCR dashboard and saw requests being logged against different providers. That’s the ideal: you shouldn’t have to think about routing. The router handles it.

Benchmarks: Cold Start vs. Hot Cache Routing Latency

I measured routing latency across three scenarios on my workstation (Ryzen 9 7950X, 64GB RAM, Windows 11):

Cold start is the only slow path — CCR compiles its routing rules and pings each provider to establish baseline health. After that, routing decisions are sub-second. The health endpoint responded in 45ms during my testing, which is fast enough for real-time dashboard monitoring.

Comparison: CCR vs. n8n vs. Composio vs. Raw

n8n is great for workflow automation — it just wasn’t built for agent routing. Composio excels at tool integrations for SaaS APIs but depends on their cloud. I covered Composio in a previous review, and it’s a solid choice if your stack is cloud-native. For Claude Code specifically, Claude Code Templates handles the config side — agent setup, MCPs, hooks — while CCR handles the routing layer. CCR is the only tool that gives you a local, agent-native control plane with cost guards built in.

If you already use n8n for non-agent workflows, they complement each other — n8n handles your business automation, CCR routes your coding agents.

Who Should Use Claude Code Router

The Bottom Line

So here’s my verdict: Claude Code Router solves a real, growing problem — the fragmentation of AI agent CLIs. It’s not a workflow builder or a SaaS integration layer. It’s a router, plain and simple, and it does that one thing well.

The 35.7K stars are earned. Install time is 30 seconds. Config is one YAML/JSON file. And once it’s running, your agents just work — routed, cost-controlled, and monitored.

If you use Claude Code, Codex, OpenCode, or Cursor CLI, install CCR today. The first time you see a simple request hit your local Ollama while a complex one routes to Sonnet — all automatically — you’ll wonder how you managed without it.

I found Chip Huyen’s AI Engineering and Valentina Alto’s Building LLM Powered Applications helpful for understanding the patterns CCR implements under the hood — multi-agent orchestration and model routing are deep topics once you get past the quick-start guide.