Claude Code Router: Setup, Model Routing, and Tradeoffs

Claude Code Router is a community-built proxy that sits between Claude Code and the model API. Instead of sending every request to Anthropic's API directly, you point Claude Code at the router, which forwards requests to whichever provider you have configured: the Anthropic API, AWS Bedrock, Google Vertex AI, or a compatible third-party gateway.

The task content, decisions, and Where we left off belong in a record that survives model changes. Keeping that record in fenbs means switching providers through the router does not mean rebuilding the project context from scratch.

What problem does Claude Code Router solve?

Some teams have an existing AWS Bedrock or Google Vertex AI agreement and need to route inference traffic through it for compliance or cost reasons. Others want to try a different provider without reconfiguring every tool that calls the Claude API. The router gives you one configuration point rather than changing environment variables in multiple places.

The router also opens up fallback strategies. If one provider is slow or unavailable, you can configure a secondary route. Whether that is worth the added setup depends on how often you need the flexibility; for most individual developers, a direct Anthropic API connection is simpler.

How do you set up Claude Code Router?

The general steps are to install the router, supply your provider credentials, configure a routing table, and then point Claude Code at the router's local endpoint.

1. Install the router. The project publishes instructions on its repository page; follow the install steps there to get the correct version for your Node.js environment.
2. Provide credentials for each provider you want to route to. The router needs API keys or role-based credentials for each backend. Keep these in environment variables, not in config files you commit.
3. Write a routing configuration that maps Claude Code's model identifiers to a provider and model. Check the router documentation for the exact format, because it can change between versions.
4. Start the router on a local port and set ANTHROPIC_BASE_URL to point Claude Code at that port. When Claude Code sends a request, the router intercepts it and forwards it to the provider you configured.
5. Test with a simple prompt before using the router on a real task. Confirm the model name in the response is the one you expected.

Because ANTHROPIC_BASE_URL redirects all of Claude Code's API traffic, make sure the router is running before you start Claude Code. If the router is down, Claude Code will fail to connect and your session will not start.

What providers can the router target?

The available targets depend on the router version and its configuration options. Common backends include the Anthropic API (the default if no router is used), AWS Bedrock with Claude models, Google Vertex AI with Claude models, and OpenRouter, which itself aggregates many providers. Verify the current list in the router's own documentation before relying on a specific backend.

What are the routing tradeoffs?

Routing through a proxy adds a layer between Claude Code and the model. That layer introduces considerations worth thinking through before you commit to using it.

• Latency. The router adds a network hop, and some backend providers have higher response times than Anthropic's direct API. Run a timing comparison on a representative task before assuming the tradeoff is acceptable.
• Capability parity. The same model identifier across different providers does not guarantee identical behavior. Bedrock and Vertex AI deployments of Claude models may be at different versions or have different rate limits than the direct API.
• Maintenance. Community tools are not supported by Anthropic. If a Claude Code release changes the API shape, the router may need an update before it works again. Track the router's release page alongside Claude Code's.
• Security. The router process can see every prompt and response that passes through it. Use it only in environments where that is acceptable and where you control who can start the router process.

How does task state survive a model switch?

When you route to a different model mid-project, the session context resets. The new model does not have memory of what the previous one said. Any decisions, accepted approaches, and working notes that lived only in the conversation are gone.

This is the same problem as switching AI apps entirely, just at the provider level. The portable AI memory guide covers why keeping the important record outside the session matters. With fenbs, the task plan, decisions, and Where we left off are available to whichever model the router sends traffic to.

How to do this with fenbs

1. Create a free account and add the project you are routing Claude Code on.
2. Connect Claude Code to fenbs from Integrations. Make sure the MCP connection is confirmed before you start routing to a different provider.
3. Before switching the router target, ask the current session to save task progress and Where we left off in fenbs.
4. Reconfigure the router to the new provider, start a fresh Claude Code session, and ask it to read the project context and rules.
5. Confirm the new session can see the task plan and decisions before giving it the next instruction.

fenbs does not know which provider the router is using and does not configure the router itself. It holds the work record. For understanding the Claude Code version you are running, see the Claude Code update guide. For the base install, see how to install Claude Code.