# Cline

Cline CLI accepts `openai` as shorthand for its OpenAI-compatible provider and stores it as `openai-compatible`. Configure it with the Pool API key, the Codex Pooler `/v1` base URL, and the model id that your assigned Pool can serve.

```bash
cline auth \
  --provider openai \
  --apikey "$CODEX_POOLER_API_KEY" \
  --baseurl https://codex-pooler.example.com/v1 \
  --modelid gpt-5.5
```

For local setup, change `--baseurl` to `http://localhost:4000/v1`.

Cline's user-facing model metadata names are `contextWindow`, `maxInputTokens`, and `maxTokens`. If you add a manual Codex Pooler model entry in Cline settings, use `contextWindow: 272000`, `maxInputTokens: 144000`, and `maxTokens: 128000` for `gpt-5.5`; Cline's compaction trigger then leaves room for a long completion inside the 272k Pooler window.

Check the headless CLI path after saving auth:

```bash
cline --provider openai \
  --model gpt-5.5 \
  --json \
  --auto-approve false \
  'Reply with exactly: cline ok'
```

For optional operator MCP in Cline CLI, add the remote server to `~/.cline/mcp.json`. Codex Pooler does not require this for model use. The VS Code extension opens its own MCP settings JSON from the Cline MCP Servers panel; use the same `mcpServers` shape there.

```json
{
  "mcpServers": {
    "codex_pooler": {
      "url": "https://codex-pooler.example.com/mcp",
      "headers": {
        "Authorization": "Bearer <operator-mcp-token>"
      },
      "disabled": false,
      "autoApprove": []
    }
  }
}
```

For local MCP setup, change the MCP `url` to `http://localhost:4000/mcp`.

Use a Pool API key for `/v1` model requests and an operator MCP token for `/mcp`. Do not reuse the Pool API key for MCP.