diff --git a/output.png b/output.png
new file mode 100644
index 0000000..87b8f1b
Binary files /dev/null and b/output.png differ
diff --git a/tensors/cli.py b/tensors/cli.py
index 5b12c12..8937f73 100644
--- a/tensors/cli.py
+++ b/tensors/cli.py
@@ -8,6 +8,7 @@ from importlib.metadata import version
 from pathlib import Path
 from typing import Annotated, Any
 
+import httpx
 import typer
 from rich.console import Console
 from rich.table import Table
@@ -1198,6 +1199,177 @@ def remote_default(
         console.print("[green]Default remote cleared.[/green]")
 
 
+# =============================================================================
+# ComfyUI Commands
+# =============================================================================
+
+comfy_app = typer.Typer(
+    name="comfy",
+    help="ComfyUI client commands.",
+    no_args_is_help=True,
+)
+app.add_typer(comfy_app, name="comfy")
+
+COMFY_DEFAULT_URL = "http://junkpile:8188"
+
+
+@comfy_app.command("status")
+def comfy_status(
+    url: Annotated[str, typer.Option("--url", "-u", help="ComfyUI server URL")] = COMFY_DEFAULT_URL,
+    json_output: Annotated[bool, typer.Option("--json", "-j", help="Output as JSON")] = False,
+) -> None:
+    """Show ComfyUI server status."""
+    try:
+        resp = httpx.get(f"{url}/system_stats", timeout=10)
+        resp.raise_for_status()
+        data = resp.json()
+    except httpx.HTTPError as e:
+        console.print(f"[red]Error: Cannot connect to ComfyUI at {url}: {e}[/red]")
+        raise typer.Exit(1) from e
+
+    if json_output:
+        console.print_json(data=data)
+        return
+
+    system = data.get("system", {})
+    devices = data.get("devices", [])
+
+    table = Table(title="ComfyUI Status", show_header=True, header_style="bold magenta")
+    table.add_column("Property", style="cyan")
+    table.add_column("Value", style="green")
+    table.add_row("URL", url)
+    table.add_row("Version", system.get("comfyui_version", "N/A"))
+    table.add_row("Python", system.get("python_version", "N/A").split()[0])
+    table.add_row("PyTorch", system.get("pytorch_version", "N/A"))
+    table.add_row("RAM Free", f"{system.get('ram_free', 0) / 1024**3:.1f} GB")
+
+    for dev in devices:
+        vram_free = dev.get("vram_free", 0) / 1024**3
+        vram_total = dev.get("vram_total", 0) / 1024**3
+        table.add_row(f"GPU {dev.get('index', 0)}", f"{dev.get('name', 'N/A')} ({vram_free:.1f}/{vram_total:.1f} GB free)")
+
+    console.print(table)
+
+
+@comfy_app.command("models")
+def comfy_models(
+    url: Annotated[str, typer.Option("--url", "-u", help="ComfyUI server URL")] = COMFY_DEFAULT_URL,
+    json_output: Annotated[bool, typer.Option("--json", "-j", help="Output as JSON")] = False,
+) -> None:
+    """List available checkpoints in ComfyUI."""
+    from tensors.comfy import ComfyClient  # noqa: PLC0415
+
+    try:
+        client = ComfyClient(url)
+        checkpoints = client.get_checkpoints()
+    except httpx.HTTPError as e:
+        console.print(f"[red]Error: {e}[/red]")
+        raise typer.Exit(1) from e
+
+    if json_output:
+        console.print_json(data={"checkpoints": checkpoints})
+        return
+
+    if not checkpoints:
+        console.print("[yellow]No checkpoints found.[/yellow]")
+        return
+
+    table = Table(title="ComfyUI Checkpoints", show_header=True, header_style="bold magenta")
+    table.add_column("#", style="dim", width=3)
+    table.add_column("Name", style="cyan")
+
+    for i, ckpt in enumerate(checkpoints, 1):
+        table.add_row(str(i), ckpt)
+
+    console.print(table)
+
+
+@comfy_app.command("loras")
+def comfy_loras(
+    url: Annotated[str, typer.Option("--url", "-u", help="ComfyUI server URL")] = COMFY_DEFAULT_URL,
+    json_output: Annotated[bool, typer.Option("--json", "-j", help="Output as JSON")] = False,
+) -> None:
+    """List available LoRAs in ComfyUI."""
+    from tensors.comfy import ComfyClient  # noqa: PLC0415
+
+    try:
+        client = ComfyClient(url)
+        loras = client.get_loras()
+    except httpx.HTTPError as e:
+        console.print(f"[red]Error: {e}[/red]")
+        raise typer.Exit(1) from e
+
+    if json_output:
+        console.print_json(data={"loras": loras})
+        return
+
+    if not loras:
+        console.print("[yellow]No LoRAs found.[/yellow]")
+        return
+
+    table = Table(title="ComfyUI LoRAs", show_header=True, header_style="bold magenta")
+    table.add_column("#", style="dim", width=3)
+    table.add_column("Name", style="cyan")
+
+    for i, lora in enumerate(loras, 1):
+        table.add_row(str(i), lora)
+
+    console.print(table)
+
+
+@comfy_app.command("generate")
+def comfy_generate(
+    prompt: Annotated[str, typer.Argument(help="Text prompt for generation")],
+    url: Annotated[str, typer.Option("--url", "-u", help="ComfyUI server URL")] = COMFY_DEFAULT_URL,
+    checkpoint: Annotated[str | None, typer.Option("-m", "--model", help="Checkpoint model name")] = None,
+    negative: Annotated[str, typer.Option("-n", "--negative", help="Negative prompt")] = "",
+    width: Annotated[int, typer.Option("-W", "--width", help="Image width")] = 512,
+    height: Annotated[int, typer.Option("-H", "--height", help="Image height")] = 512,
+    steps: Annotated[int, typer.Option("--steps", help="Sampling steps")] = 20,
+    cfg: Annotated[float, typer.Option("--cfg", help="CFG scale")] = 7.0,
+    seed: Annotated[int, typer.Option("-s", "--seed", help="RNG seed (-1 for random)")] = -1,
+    sampler: Annotated[str, typer.Option("--sampler", help="Sampler name")] = "euler_ancestral",
+    output: Annotated[Path | None, typer.Option("-o", "--output", help="Output file path")] = None,
+    json_output: Annotated[bool, typer.Option("--json", "-j", help="Output as JSON")] = False,
+) -> None:
+    """Generate an image using ComfyUI."""
+    from tensors.comfy import ComfyClient  # noqa: PLC0415
+
+    try:
+        client = ComfyClient(url)
+
+        console.print(f"[cyan]Generating with ComfyUI at {url}...[/cyan]")
+        result = client.generate(
+            prompt=prompt,
+            negative_prompt=negative,
+            checkpoint=checkpoint,
+            width=width,
+            height=height,
+            steps=steps,
+            cfg=cfg,
+            seed=seed,
+            sampler=sampler,
+        )
+    except Exception as e:
+        console.print(f"[red]Error: {e}[/red]")
+        raise typer.Exit(1) from e
+
+    if json_output:
+        console.print_json(data=result)
+        return
+
+    console.print(f"[green]Generated![/green] Seed: {result['seed']}, Checkpoint: {result['checkpoint']}")
+
+    if result["images"]:
+        img_info = result["images"][0]
+        console.print(f"[dim]Image: {img_info['filename']}[/dim]")
+
+        if output:
+            img_data = client.get_image(img_info["filename"], img_info["subfolder"], img_info["type"])
+            output.write_bytes(img_data)
+            console.print(f"[green]Saved to:[/green] {output}")
+
+
 def main() -> int:
     """Main entry point."""
     # Handle legacy invocation: tsr <file.safetensors> -> tsr info <file>
@@ -1216,6 +1388,7 @@ def main() -> int:
         "images",
         "models",
         "remote",
+        "comfy",
     )
     if len(sys.argv) > 1 and not sys.argv[1].startswith("-"):
         arg = sys.argv[1]
diff --git a/tensors/comfy.py b/tensors/comfy.py
new file mode 100644
index 0000000..33c88f6
--- /dev/null
+++ b/tensors/comfy.py
@@ -0,0 +1,190 @@
+"""Simple ComfyUI client for basic txt2img generation."""
+
+from __future__ import annotations
+
+import json
+import time
+import uuid
+from pathlib import Path
+from typing import Any
+
+import httpx
+
+DEFAULT_WORKFLOW = {
+    "3": {
+        "class_type": "KSampler",
+        "inputs": {
+            "cfg": 7,
+            "denoise": 1,
+            "latent_image": ["5", 0],
+            "model": ["4", 0],
+            "negative": ["7", 0],
+            "positive": ["6", 0],
+            "sampler_name": "euler_ancestral",
+            "scheduler": "normal",
+            "seed": -1,
+            "steps": 20,
+        },
+    },
+    "4": {
+        "class_type": "CheckpointLoaderSimple",
+        "inputs": {"ckpt_name": ""},
+    },
+    "5": {
+        "class_type": "EmptyLatentImage",
+        "inputs": {"batch_size": 1, "height": 512, "width": 512},
+    },
+    "6": {
+        "class_type": "CLIPTextEncode",
+        "inputs": {"clip": ["4", 1], "text": ""},
+    },
+    "7": {
+        "class_type": "CLIPTextEncode",
+        "inputs": {"clip": ["4", 1], "text": ""},
+    },
+    "8": {
+        "class_type": "VAEDecode",
+        "inputs": {"samples": ["3", 0], "vae": ["4", 2]},
+    },
+    "9": {
+        "class_type": "SaveImage",
+        "inputs": {"filename_prefix": "comfy", "images": ["8", 0]},
+    },
+}
+
+
+class ComfyClient:
+    """Simple ComfyUI API client."""
+
+    def __init__(self, base_url: str = "http://127.0.0.1:8188", timeout: float = 300.0) -> None:
+        self.base_url = base_url.rstrip("/")
+        self.timeout = timeout
+        self.client_id = str(uuid.uuid4())
+
+    def get_checkpoints(self) -> list[str]:
+        """List available checkpoint models."""
+        resp = httpx.get(f"{self.base_url}/object_info/CheckpointLoaderSimple", timeout=10)
+        resp.raise_for_status()
+        data = resp.json()
+        return list(data.get("CheckpointLoaderSimple", {}).get("input", {}).get("required", {}).get("ckpt_name", [[]])[0])
+
+    def get_loras(self) -> list[str]:
+        """List available LoRAs."""
+        resp = httpx.get(f"{self.base_url}/object_info/LoraLoader", timeout=10)
+        resp.raise_for_status()
+        data = resp.json()
+        return list(data.get("LoraLoader", {}).get("input", {}).get("required", {}).get("lora_name", [[]])[0])
+
+    def get_samplers(self) -> list[str]:
+        """List available samplers."""
+        resp = httpx.get(f"{self.base_url}/object_info/KSampler", timeout=10)
+        resp.raise_for_status()
+        data = resp.json()
+        return list(data.get("KSampler", {}).get("input", {}).get("required", {}).get("sampler_name", [[]])[0])
+
+    def queue_prompt(self, workflow: dict[str, Any]) -> str:
+        """Queue a prompt and return the prompt_id."""
+        payload = {"prompt": workflow, "client_id": self.client_id}
+        resp = httpx.post(f"{self.base_url}/prompt", json=payload, timeout=30)
+        resp.raise_for_status()
+        return str(resp.json()["prompt_id"])
+
+    def get_history(self, prompt_id: str) -> dict[str, Any] | None:
+        """Get history for a prompt_id."""
+        resp = httpx.get(f"{self.base_url}/history/{prompt_id}", timeout=10)
+        if resp.is_success:
+            data = resp.json()
+            return dict(data.get(prompt_id, {})) if prompt_id in data else None
+        return None
+
+    def wait_for_completion(self, prompt_id: str, poll_interval: float = 0.5) -> dict[str, Any]:
+        """Poll until the prompt completes."""
+        start = time.time()
+        while time.time() - start < self.timeout:
+            history = self.get_history(prompt_id)
+            if history and history.get("outputs"):
+                return history
+            time.sleep(poll_interval)
+        raise TimeoutError(f"Prompt {prompt_id} did not complete within {self.timeout}s")
+
+    def get_image(self, filename: str, subfolder: str = "", folder_type: str = "output") -> bytes:
+        """Download an image from ComfyUI."""
+        params = {"filename": filename, "subfolder": subfolder, "type": folder_type}
+        resp = httpx.get(f"{self.base_url}/view", params=params, timeout=30)
+        resp.raise_for_status()
+        return resp.content
+
+    def generate(
+        self,
+        prompt: str,
+        negative_prompt: str = "",
+        checkpoint: str | None = None,
+        width: int = 512,
+        height: int = 512,
+        steps: int = 20,
+        cfg: float = 7.0,
+        seed: int = -1,
+        sampler: str = "euler_a",
+        scheduler: str = "normal",
+    ) -> dict[str, Any]:
+        """Generate an image with a simple txt2img workflow."""
+        # Use first checkpoint if not specified
+        if not checkpoint:
+            checkpoints = self.get_checkpoints()
+            if not checkpoints:
+                raise ValueError("No checkpoints available")
+            checkpoint = checkpoints[0]
+
+        # Build workflow
+        workflow = json.loads(json.dumps(DEFAULT_WORKFLOW))
+        workflow["4"]["inputs"]["ckpt_name"] = checkpoint
+        workflow["5"]["inputs"]["width"] = width
+        workflow["5"]["inputs"]["height"] = height
+        workflow["6"]["inputs"]["text"] = prompt
+        workflow["7"]["inputs"]["text"] = negative_prompt
+        workflow["3"]["inputs"]["steps"] = steps
+        workflow["3"]["inputs"]["cfg"] = cfg
+        workflow["3"]["inputs"]["seed"] = seed if seed >= 0 else int(time.time() * 1000) % (2**32)
+        workflow["3"]["inputs"]["sampler_name"] = sampler
+        workflow["3"]["inputs"]["scheduler"] = scheduler
+
+        # Queue and wait
+        prompt_id = self.queue_prompt(workflow)
+        history = self.wait_for_completion(prompt_id)
+
+        # Extract output images
+        outputs = history.get("outputs", {})
+        images = []
+        for _node_id, node_output in outputs.items():
+            if "images" in node_output:
+                for img in node_output["images"]:
+                    images.append({
+                        "filename": img["filename"],
+                        "subfolder": img.get("subfolder", ""),
+                        "type": img.get("type", "output"),
+                    })
+
+        return {
+            "prompt_id": prompt_id,
+            "images": images,
+            "checkpoint": checkpoint,
+            "seed": workflow["3"]["inputs"]["seed"],
+        }
+
+    def generate_and_save(
+        self,
+        prompt: str,
+        output_path: str | Path,
+        **kwargs: Any,
+    ) -> Path:
+        """Generate an image and save it locally."""
+        result = self.generate(prompt, **kwargs)
+        if not result["images"]:
+            raise RuntimeError("No images generated")
+
+        img_info = result["images"][0]
+        img_data = self.get_image(img_info["filename"], img_info["subfolder"], img_info["type"])
+
+        output = Path(output_path)
+        output.write_bytes(img_data)
+        return output