Claude Code.

Configure OpenCode

Once, as its page explains, or by letting the NaN CLI do it.

Check that it answers without an interface

opencode run --agent plan -m nan/deepseek-v4-flash "Summarize in three lines what this repository does."

Three things about that command:

• run is the headless mode: it does the task, writes the answer and exits.
• -m takes the model as provider/model, where the provider is the name you gave it in your opencode.json, nan if you followed our page.
• --agent plan leaves OpenCode in read-only mode. Without it, it starts with its default agent, which can edit files and run commands. For delegating a review or a summary, that is not what you want.

The answer comes back on standard output, preceded by the tools it used:

> plan · deepseek-v4-flash
→ Read src/lib/modelCatalog.ts
It is the single source of truth for the model catalog...

Ask Claude Code for it

Inside a Claude Code session, say it plainly:

Use `opencode run --agent plan -m nan/deepseek-v4-flash` to review
src/parser.ts and tell me which cases it is not covering.

Claude Code runs the command, reads what OpenCode answers and carries on from there. The first time, it will ask for permission to run it.

It works well for what is long to read and cheap to summarize: reviewing a big file, making a first draft, summarizing documentation, comparing two versions. Claude Code keeps the coordination and the fine edits.

Two options that help once you get a taste for it:

• -f file attaches specific files, instead of making it look for them.
• -c continues OpenCode’s last conversation, so you can follow up without explaining everything again.

Install the gateway

LiteLLM exposes a /v1/messages endpoint in Anthropic’s format and translates it into OpenAI’s before forwarding it.

pip install "litellm[proxy]"

Configure the gateway

Create a litellm.config.yaml wherever suits you:

model_list:
  - model_name: nan-coder
    litellm_params:
      model: openai/glm5.3-flash
      api_base: https://api.nan.builders/v1
      api_key: os.environ/NAN_API_KEY

  - model_name: nan-general
    litellm_params:
      model: openai/deepseek-v4-flash
      api_base: https://api.nan.builders/v1
      api_key: os.environ/NAN_API_KEY

general_settings:
  master_key: sk-local-change-this

The openai/ prefix tells LiteLLM which format to speak to NaN in. What comes after the prefix is the model id as it is, and model_name is the name you will see it under from Claude Code.

The master_key is a key you make up for your local gateway. It is not your NaN key, and it must not be: only the LiteLLM process knows that one.

Start the gateway

litellm --config litellm.config.yaml --port 4000

Leave it running in its own terminal.

Point Claude Code at the gateway

export ANTHROPIC_BASE_URL="http://localhost:4000"
export ANTHROPIC_AUTH_TOKEN="sk-local-change-this"
export ANTHROPIC_MODEL="nan-coder"

claude

Use ANTHROPIC_AUTH_TOKEN and not ANTHROPIC_API_KEY: it is the variable Claude Code sends as the Authorization header when the base URL is not Anthropic’s.

If you would rather pick the model per session than fix it through the environment, leave ANTHROPIC_MODEL out and start with claude --model nan-coder.

Check that it works

With the gateway up:

curl http://localhost:4000/v1/messages \
  -H "Authorization: Bearer sk-local-change-this" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "nan-coder",
    "max_tokens": 64,
    "messages": [{ "role": "user", "content": "Say hello." }]
  }'

If that answers, so will Claude Code. If it returns an authentication error, the thing that is wrong is the master_key; if it returns 404 model_not_found, what is wrong is the NaN id inside litellm_params.