---
summary: "CLI backends: local AI CLI fallback with optional MCP tool bridge"
read_when:
  - You want a reliable fallback when API providers fail
  - You are running Codex CLI or other local AI CLIs and want to reuse them
  - You want to understand the MCP loopback bridge for CLI backend tool access
title: "CLI Backends"
---

# CLI backends (fallback runtime)

KaijiBot can run **local AI CLIs** as a **text-only fallback** when API providers are down,
rate-limited, or temporarily misbehaving. This is intentionally conservative:

- **KaijiBot tools are not injected directly**, but backends with `bundleMcp: true`
  can receive gateway tools via a loopback MCP bridge.
- **JSONL streaming** for CLIs that support it.
- **Sessions are supported** (so follow-up turns stay coherent).
- **Images can be passed through** if the CLI accepts image paths.

This is designed as a **safety net** rather than a primary path. Use it when you
want “always works” text responses without relying on external APIs.

If you want a full harness runtime with ACP session controls, background tasks,
thread/conversation binding, and persistent external coding sessions, use
[ACP Agents](/tools/acp-agents) instead. CLI backends are not ACP.

## Beginner-friendly quick start

You can use Codex CLI **without any config** (the bundled OpenAI plugin
registers a default backend):

```bash
kaijibot agent --message "hi" --model codex-cli/gpt-5.4
```

If your gateway runs under launchd/systemd and PATH is minimal, add just the
command path:

```json5
{
  agents: {
    defaults: {
      cliBackends: {
        "codex-cli": {
          command: "/opt/homebrew/bin/codex",
        },
      },
    },
  },
}
```

That’s it. No keys, no extra auth config needed beyond the CLI itself.

If you use a bundled CLI backend as the **primary message provider** on a
gateway host, KaijiBot now auto-loads the owning bundled plugin when your config
explicitly references that backend in a model ref or under
`agents.defaults.cliBackends`.

## Using it as a fallback

Add a CLI backend to your fallback list so it only runs when primary models fail:

```json5
{
  agents: {
    defaults: {
      model: {
        primary: "anthropic/claude-opus-4-6",
        fallbacks: ["codex-cli/gpt-5.4"],
      },
      models: {
        "anthropic/claude-opus-4-6": { alias: "Opus" },
        "codex-cli/gpt-5.4": {},
      },
    },
  },
}
```

Notes:

- If you use `agents.defaults.models` (allowlist), you must include your CLI backend models there too.
- If the primary provider fails (auth, rate limits, timeouts), KaijiBot will
  try the CLI backend next.

## Configuration overview

All CLI backends live under:

```
agents.defaults.cliBackends
```

Each entry is keyed by a **provider id** (e.g. `codex-cli`, `my-cli`).
The provider id becomes the left side of your model ref:

```
<provider>/<model>
```

### Example configuration

```json5
{
  agents: {
    defaults: {
      cliBackends: {
        "codex-cli": {
          command: "/opt/homebrew/bin/codex",
        },
        "my-cli": {
          command: "my-cli",
          args: ["--json"],
          output: "json",
          input: "arg",
          modelArg: "--model",
          modelAliases: {
            "claude-opus-4-6": "opus",
            "claude-sonnet-4-6": "sonnet",
          },
          sessionArg: "--session",
          sessionMode: "existing",
          sessionIdFields: ["session_id", "conversation_id"],
          systemPromptArg: "--system",
          // Codex-style CLIs can point at a prompt file instead:
          // systemPromptFileConfigArg: "-c",
          // systemPromptFileConfigKey: "model_instructions_file",
          systemPromptWhen: "first",
          imageArg: "--image",
          imageMode: "repeat",
          serialize: true,
        },
      },
    },
  },
}
```

## How it works

1. **Selects a backend** based on the provider prefix (`codex-cli/...`).
2. **Builds a system prompt** using the same KaijiBot prompt + workspace context.
3. **Executes the CLI** with a session id (if supported) so history stays consistent.
4. **Parses output** (JSON or plain text) and returns the final text.
5. **Persists session ids** per backend, so follow-ups reuse the same CLI session.

<Note>
The bundled Anthropic `claude-cli` backend is supported again. Anthropic staff
told us KaijiBot-style Claude CLI usage is allowed again, so KaijiBot treats
`claude -p` usage as sanctioned for this integration unless Anthropic publishes
a new policy.
</Note>

The bundled OpenAI `codex-cli` backend passes KaijiBot's system prompt through
Codex's `model_instructions_file` config override (`-c
model_instructions_file="..."`). Codex does not expose a Claude-style
`--append-system-prompt` flag, so KaijiBot writes the assembled prompt to a
temporary file for each fresh Codex CLI session.

## Sessions

- If the CLI supports sessions, set `sessionArg` (e.g. `--session-id`) or
  `sessionArgs` (placeholder `{sessionId}`) when the ID needs to be inserted
  into multiple flags.
- If the CLI uses a **resume subcommand** with different flags, set
  `resumeArgs` (replaces `args` when resuming) and optionally `resumeOutput`
  (for non-JSON resumes).
- `sessionMode`:
  - `always`: always send a session id (new UUID if none stored).
  - `existing`: only send a session id if one was stored before.
  - `none`: never send a session id.

Serialization notes:

- `serialize: true` keeps same-lane runs ordered.
- Most CLIs serialize on one provider lane.
- KaijiBot drops stored CLI session reuse when the backend auth state changes, including relogin, token rotation, or a changed auth profile credential.

## Images (pass-through)

If your CLI accepts image paths, set `imageArg`:

```json5
imageArg: "--image",
imageMode: "repeat"
```

KaijiBot will write base64 images to temp files. If `imageArg` is set, those
paths are passed as CLI args. If `imageArg` is missing, KaijiBot appends the
file paths to the prompt (path injection), which is enough for CLIs that auto-
load local files from plain paths.

## Inputs / outputs

- `output: "json"` (default) tries to parse JSON and extract text + session id.
- For Gemini CLI JSON output, KaijiBot reads reply text from `response` and
  usage from `stats` when `usage` is missing or empty.
- `output: "jsonl"` parses JSONL streams (for example Codex CLI `--json`) and extracts the final agent message plus session
  identifiers when present.
- `output: "text"` treats stdout as the final response.

Input modes:

- `input: "arg"` (default) passes the prompt as the last CLI arg.
- `input: "stdin"` sends the prompt via stdin.
- If the prompt is very long and `maxPromptArgChars` is set, stdin is used.

## Defaults (plugin-owned)

The bundled OpenAI plugin also registers a default for `codex-cli`:

- `command: "codex"`
- `args: ["exec","--json","--color","never","--sandbox","workspace-write","--skip-git-repo-check"]`
- `resumeArgs: ["exec","resume","{sessionId}","--color","never","--sandbox","workspace-write","--skip-git-repo-check"]`
- `output: "jsonl"`
- `resumeOutput: "text"`
- `modelArg: "--model"`
- `imageArg: "--image"`
- `sessionMode: "existing"`

The bundled Google plugin also registers a default for `google-gemini-cli`:

- `command: "gemini"`
- `args: ["--output-format", "json", "--prompt", "{prompt}"]`
- `resumeArgs: ["--resume", "{sessionId}", "--output-format", "json", "--prompt", "{prompt}"]`
- `imageArg: "@"`
- `imagePathScope: "workspace"`
- `modelArg: "--model"`
- `sessionMode: "existing"`
- `sessionIdFields: ["session_id", "sessionId"]`

Prerequisite: the local Gemini CLI must be installed and available as
`gemini` on `PATH` (`brew install gemini-cli` or
`npm install -g @google/gemini-cli`).

Gemini CLI JSON notes:

- Reply text is read from the JSON `response` field.
- Usage falls back to `stats` when `usage` is absent or empty.
- `stats.cached` is normalized into KaijiBot `cacheRead`.
- If `stats.input` is missing, KaijiBot derives input tokens from
  `stats.input_tokens - stats.cached`.

Override only if needed (common: absolute `command` path).

## Plugin-owned defaults

CLI backend defaults are now part of the plugin surface:

- Plugins register them with `api.registerCliBackend(...)`.
- The backend `id` becomes the provider prefix in model refs.
- User config in `agents.defaults.cliBackends.<id>` still overrides the plugin default.
- Backend-specific config cleanup stays plugin-owned through the optional
  `normalizeConfig` hook.

## Bundle MCP overlays

CLI backends do **not** receive KaijiBot tool calls directly, but a backend can
opt into a generated MCP config overlay with `bundleMcp: true`.

Current bundled behavior:

- `claude-cli`: generated strict MCP config file
- `codex-cli`: inline config overrides for `mcp_servers`
- `google-gemini-cli`: generated Gemini system settings file

When bundle MCP is enabled, KaijiBot:

- spawns a loopback HTTP MCP server that exposes gateway tools to the CLI process
- authenticates the bridge with a per-session token (`KAIJIBOT_MCP_TOKEN`)
- scopes tool access to the current session, account, and channel context
- loads enabled bundle-MCP servers for the current workspace
- merges them with any existing backend MCP config/settings shape
- rewrites the launch config using the backend-owned integration mode from the owning extension

If no MCP servers are enabled, KaijiBot still injects a strict config when a
backend opts into bundle MCP so background runs stay isolated.

## Limitations

- **No direct KaijiBot tool calls.** KaijiBot does not inject tool calls into
  the CLI backend protocol. Backends only see gateway tools when they opt into
  `bundleMcp: true`.
- **Streaming is backend-specific.** Some backends stream JSONL; others buffer
  until exit.
- **Structured outputs** depend on the CLI’s JSON format.
- **Codex CLI sessions** resume via text output (no JSONL), which is less
  structured than the initial `--json` run. KaijiBot sessions still work
  normally.

## Troubleshooting

- **CLI not found**: set `command` to a full path.
- **Wrong model name**: use `modelAliases` to map `provider/model` → CLI model.
- **No session continuity**: ensure `sessionArg` is set and `sessionMode` is not
  `none` (Codex CLI currently cannot resume with JSON output).
- **Images ignored**: set `imageArg` (and verify CLI supports file paths).
