Why shunt

shunt is a spec-compliant Claude Code LLM gateway: a transparent proxy that, for the models you map, diverts inference to another LLM provider at the inference layer. It routes by the request’s model id — by default, everything else passes through to Anthropic unchanged (the “shunt”; the fallback is configurable via server.default_provider).

The name is the mechanism: an electrical/railway shunt diverts a selected part of the flow onto a parallel path. Here, a mapped model’s inference is diverted to another provider while Claude Code’s tools and skills stay intact.

How it works

Claude Code sends every turn to the Anthropic API. shunt sits in front (via ANTHROPIC_BASE_URL) and, for the models you map, diverts their inference to another provider (OpenAI, Codex/ChatGPT, …). Because routing happens at the HTTP/inference layer — not by handing the task off to a different CLI — the session keeps running inside Claude Code’s harness: same tool loop, same preloaded skills, same bundled-script path resolution. Only token generation is outsourced.

Contrast this with handing a subagent off to another runtime (like the Codex CLI), which cuts higher in the stack and drops persona and preloaded skills.

Per-model, not per-agent — and not a global swap

Most Claude Code proxies route all traffic to one alternative provider (a global model swap). shunt’s focus is selective, per-model diversion driven by the request’s model id: keep the main session on Claude, and shunt only the models you name onto other providers.

Selectivity is decided in Claude Code itself, which already lets you choose a model per context:

• the /model picker for the main session,
• a subagent definition’s model: frontmatter,
• CLAUDE_CODE_SUBAGENT_MODEL for all subagents,
• ANTHROPIC_CUSTOM_MODEL_OPTION to add a custom entry to the picker.

shunt just honors the model id it receives — no fragile per-agent system-prompt fingerprinting. That same selectivity reaches down to individual agents without shunt ever inspecting who the caller is.

What shunt implements

• POST /v1/messages — inference, routed per the request’s model id. Unmapped models are forwarded to Anthropic byte-for-byte with the caller’s own credential.
• Anthropic Messages ⇄ OpenAI Responses translation — for mapped OpenAI-family models, including streaming.
• ChatGPT subscription reuse — the codex provider reuses (and auto-refreshes) the Codex CLI’s ~/.codex/auth.json login.
• GET /v1/models — model discovery for Claude-named aliases.
• Token counting — local tiktoken counts for translated providers, exact upstream counts for passthrough.
• Streaming resilience — SSE keepalive pings so proxies like Cloudflare don’t kill long reasoning stretches.
• Optional inbound auth — per-client tokens for shared deployments.

Ready to try it? Head to Installation.