diff --git a/README.md b/README.md
index 6773111..1dfefbd 100644
--- a/README.md
+++ b/README.md
@@ -13,6 +13,9 @@ uvx noaa-tides
 # Or add to Claude Code
 claude mcp add noaa-tides -- uvx noaa-tides
 
+# With visualization support (charts)
+uv pip install noaa-tides[viz]
+
 # Local development
 uv run noaa-tides
 ```
@@ -174,6 +177,39 @@ Fires 6 parallel API calls (predictions, water level, water temp, air temp, wind
 
 Best starting point for trip planning or safety assessments.
 
+### `visualize_tides` — Tide prediction chart
+
+```
+visualize_tides(station_id="9447130", hours=48, format="png")
+```
+
+Generates a tide prediction chart with the water level curve, high/low markers, and optional observed water level overlay. PNG returns an inline image via MCP; HTML saves an interactive Plotly chart to `artifacts/charts/`.
+
+![Seattle tide predictions — 48-hour forecast with predicted curve (blue), observed overlay (teal dashed), and high/low markers](examples/tide-chart-seattle.png)
+
+Parameters:
+- `hours` — forecast window (default 48)
+- `include_observed` — overlay actual readings (default true)
+- `format` — `"png"` (inline image) or `"html"` (interactive file)
+
+Requires `noaa-tides[viz]` — install with `uv pip install noaa-tides[viz]`.
+
+### `visualize_conditions` — Multi-panel conditions dashboard
+
+```
+visualize_conditions(station_id="9447130", hours=24, format="png")
+```
+
+Generates a multi-panel dashboard with up to 4 panels: tide predictions + observed overlay, wind speed/gust, air/water temperature, and barometric pressure with trend indicator. Products unavailable at a station are omitted.
+
+![Seattle marine conditions — 4-panel dashboard showing tides, wind, temperature, and barometric pressure](examples/conditions-dashboard-seattle.png)
+
+Parameters:
+- `hours` — data window (default 24)
+- `format` — `"png"` (inline image) or `"html"` (interactive file)
+
+Requires `noaa-tides[viz]`.
+
 ## Resources
 
 | URI | Description |
@@ -220,7 +256,7 @@ marine_safety_check(station_id="9447130")
 git clone <repo-url> && cd noaa-tides
 uv sync --dev
 
-# Run tests (13 tests, mock client, no network)
+# Run tests (mock client, no network)
 uv run pytest tests/ -v
 
 # Lint
diff --git a/examples/conditions-dashboard-seattle.png b/examples/conditions-dashboard-seattle.png
new file mode 100644
index 0000000..655da06
Binary files /dev/null and b/examples/conditions-dashboard-seattle.png differ
diff --git a/examples/tide-chart-seattle.png b/examples/tide-chart-seattle.png
new file mode 100644
index 0000000..78dbd19
Binary files /dev/null and b/examples/tide-chart-seattle.png differ
diff --git a/pyproject.toml b/pyproject.toml
index 9424e6f..8bfda3d 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -8,6 +8,9 @@ dependencies = ["fastmcp>=3.0.1"]
 readme = "README.md"
 license = "MIT"
 
+[project.optional-dependencies]
+viz = ["matplotlib>=3.8", "plotly>=5.18"]
+
 [project.scripts]
 noaa-tides = "noaa_tides.server:main"
 
@@ -29,4 +32,4 @@ select = ["E", "F", "I", "W"]
 asyncio_mode = "auto"
 
 [dependency-groups]
-dev = ["pytest>=8", "pytest-asyncio>=0.24", "ruff>=0.9"]
+dev = ["pytest>=8", "pytest-asyncio>=0.24", "ruff>=0.9", "noaa-tides[viz]"]
diff --git a/src/noaa_tides/charts/__init__.py b/src/noaa_tides/charts/__init__.py
new file mode 100644
index 0000000..6b356df
--- /dev/null
+++ b/src/noaa_tides/charts/__init__.py
@@ -0,0 +1,33 @@
+"""Chart rendering for NOAA tide and conditions data.
+
+Optional dependency — requires noaa-tides[viz] to be installed.
+"""
+
+# Marine color palette — shared across all chart renderers
+OCEAN_BLUE = "#1B4F72"
+TEAL = "#148F77"
+SLATE = "#5D6D7E"
+SAND = "#D4A017"
+CORAL = "#E74C3C"
+BG_COLOR = "#FAFAFA"
+GRID_COLOR = "#E0E0E0"
+
+
+def check_deps(format: str) -> None:
+    """Raise ValueError with install hint if visualization deps are missing."""
+    if format == "png":
+        try:
+            import matplotlib  # noqa: F401
+        except ImportError:
+            raise ValueError(
+                "PNG charts require matplotlib. Install with: "
+                "uv pip install noaa-tides[viz]"
+            )
+    elif format == "html":
+        try:
+            import plotly  # noqa: F401
+        except ImportError:
+            raise ValueError(
+                "HTML charts require plotly. Install with: "
+                "uv pip install noaa-tides[viz]"
+            )
diff --git a/src/noaa_tides/charts/conditions.py b/src/noaa_tides/charts/conditions.py
new file mode 100644
index 0000000..f37c2c1
--- /dev/null
+++ b/src/noaa_tides/charts/conditions.py
@@ -0,0 +1,387 @@
+"""Multi-panel conditions dashboard — tide + wind + temperature + pressure."""
+
+import io
+from datetime import datetime
+
+from noaa_tides.charts import BG_COLOR, CORAL, GRID_COLOR, OCEAN_BLUE, SAND, SLATE, TEAL
+
+
+def _parse_time_series(data: list[dict], value_key: str = "v") -> tuple[list, list]:
+    """Extract (times, values) from NOAA data records, skipping blanks."""
+    times = []
+    values = []
+    for d in data:
+        val = d.get(value_key)
+        if val is None or val == "":
+            continue
+        times.append(datetime.strptime(d["t"], "%Y-%m-%d %H:%M"))
+        values.append(float(val))
+    return times, values
+
+
+def _parse_wind(data: list[dict]) -> dict:
+    """Extract wind speed, gust, and direction from wind records."""
+    times = []
+    speeds = []
+    gusts = []
+    directions = []
+    for d in data:
+        if d.get("s") is None or d["s"] == "":
+            continue
+        times.append(datetime.strptime(d["t"], "%Y-%m-%d %H:%M"))
+        speeds.append(float(d["s"]))
+        gusts.append(float(d.get("g", d["s"])))
+        directions.append(d.get("dr", ""))
+    return {"times": times, "speeds": speeds, "gusts": gusts, "directions": directions}
+
+
+def render_conditions_png(snapshot: dict, station_name: str = "") -> bytes:
+    """Render a multi-panel conditions dashboard as PNG bytes.
+
+    Args:
+        snapshot: Dict from marine_conditions_snapshot with predictions, water_level,
+                  wind, air_temperature, water_temperature, air_pressure keys.
+        station_name: Station name for the chart title.
+
+    Returns:
+        PNG image bytes.
+    """
+    import matplotlib
+
+    matplotlib.use("Agg")
+    import matplotlib.dates as mdates
+    import matplotlib.pyplot as plt
+
+    # Determine which panels we can show (some products may be unavailable)
+    has_predictions = "predictions" in snapshot
+    has_water_level = "water_level" in snapshot
+    has_wind = "wind" in snapshot
+    has_air_temp = "air_temperature" in snapshot
+    has_water_temp = "water_temperature" in snapshot
+    has_pressure = "air_pressure" in snapshot
+
+    panels = []
+    if has_predictions or has_water_level:
+        panels.append("tide")
+    if has_wind:
+        panels.append("wind")
+    if has_air_temp or has_water_temp:
+        panels.append("temp")
+    if has_pressure:
+        panels.append("pressure")
+
+    if not panels:
+        # Nothing to plot — return a minimal placeholder
+        fig, ax = plt.subplots(figsize=(10, 3), facecolor=BG_COLOR)
+        ax.text(
+            0.5, 0.5, "No data available for visualization",
+            transform=ax.transAxes, ha="center", va="center", fontsize=14, color=SLATE,
+        )
+        ax.set_facecolor(BG_COLOR)
+        ax.axis("off")
+        buf = io.BytesIO()
+        fig.savefig(buf, format="png", dpi=150, facecolor=BG_COLOR)
+        plt.close(fig)
+        buf.seek(0)
+        return buf.getvalue()
+
+    n_panels = len(panels)
+    fig, axes = plt.subplots(
+        n_panels, 1, figsize=(12, 3.5 * n_panels), facecolor=BG_COLOR, sharex=True,
+    )
+    if n_panels == 1:
+        axes = [axes]
+
+    date_fmt = mdates.DateFormatter("%b %d\n%H:%M")
+
+    for i, panel in enumerate(panels):
+        ax = axes[i]
+        ax.set_facecolor(BG_COLOR)
+        ax.grid(True, alpha=0.3, color=GRID_COLOR, zorder=0)
+        ax.tick_params(colors=SLATE, labelsize=8)
+
+        if panel == "tide":
+            # Predictions line
+            if has_predictions:
+                preds = snapshot["predictions"].get("predictions", [])
+                if preds:
+                    from noaa_tides.charts.tides import _parse_predictions
+
+                    p_times, p_values, markers = _parse_predictions(preds)
+                    ax.plot(
+                        p_times, p_values, color=OCEAN_BLUE, linewidth=2,
+                        label="Predicted", zorder=3,
+                    )
+                    for m in markers:
+                        is_high = m["type"] == "H"
+                        color = SAND if is_high else CORAL
+                        ax.plot(
+                            m["time"], m["value"], "o", color=color, markersize=6, zorder=4,
+                        )
+            # Observed overlay
+            if has_water_level:
+                obs_data = snapshot["water_level"].get("data", [])
+                if obs_data:
+                    from noaa_tides.charts.tides import _parse_observed
+
+                    o_times, o_values = _parse_observed(obs_data)
+                    if o_times:
+                        ax.plot(
+                            o_times, o_values, color=TEAL, linewidth=1.5,
+                            linestyle="--", alpha=0.8, label="Observed", zorder=2,
+                        )
+            ax.axhline(y=0, color=SLATE, linewidth=0.5, alpha=0.4, zorder=1)
+            ax.set_ylabel("Water Level (ft)", fontsize=9, color=SLATE)
+            ax.legend(loc="upper right", fontsize=8, framealpha=0.9)
+            ax.set_title("Tides", fontsize=10, fontweight="bold", color=OCEAN_BLUE, loc="left")
+
+        elif panel == "wind":
+            wind = _parse_wind(snapshot["wind"].get("data", []))
+            if wind["times"]:
+                ax.plot(
+                    wind["times"], wind["speeds"], color=OCEAN_BLUE, linewidth=1.5,
+                    label="Speed", zorder=3,
+                )
+                ax.fill_between(
+                    wind["times"], wind["speeds"], wind["gusts"],
+                    alpha=0.2, color=CORAL, label="Gust", zorder=2,
+                )
+                ax.plot(
+                    wind["times"], wind["gusts"], color=CORAL, linewidth=1,
+                    linestyle="--", alpha=0.6, zorder=2,
+                )
+            ax.set_ylabel("Wind (kn)", fontsize=9, color=SLATE)
+            ax.legend(loc="upper right", fontsize=8, framealpha=0.9)
+            ax.set_title("Wind", fontsize=10, fontweight="bold", color=OCEAN_BLUE, loc="left")
+
+        elif panel == "temp":
+            if has_air_temp:
+                air_data = snapshot["air_temperature"].get("data", [])
+                at, av = _parse_time_series(air_data)
+                if at:
+                    ax.plot(at, av, color=CORAL, linewidth=1.5, label="Air", zorder=3)
+            if has_water_temp:
+                water_data = snapshot["water_temperature"].get("data", [])
+                wt, wv = _parse_time_series(water_data)
+                if wt:
+                    ax.plot(wt, wv, color=TEAL, linewidth=1.5, label="Water", zorder=3)
+            ax.set_ylabel("Temp (\u00b0F)", fontsize=9, color=SLATE)
+            ax.legend(loc="upper right", fontsize=8, framealpha=0.9)
+            ax.set_title(
+                "Temperature", fontsize=10, fontweight="bold", color=OCEAN_BLUE, loc="left",
+            )
+
+        elif panel == "pressure":
+            press_data = snapshot["air_pressure"].get("data", [])
+            pt, pv = _parse_time_series(press_data)
+            if pt:
+                ax.plot(pt, pv, color=SLATE, linewidth=1.5, zorder=3)
+                # Trend indicator: compare first and last
+                if len(pv) >= 2:
+                    diff = pv[-1] - pv[0]
+                    arrow = "\u2191" if diff > 0.5 else ("\u2193" if diff < -0.5 else "\u2192")
+                    ax.annotate(
+                        f"{arrow} {diff:+.1f} mb",
+                        xy=(pt[-1], pv[-1]),
+                        fontsize=9,
+                        fontweight="bold",
+                        color=OCEAN_BLUE,
+                        xytext=(10, 0),
+                        textcoords="offset points",
+                    )
+            ax.set_ylabel("Pressure (mb)", fontsize=9, color=SLATE)
+            ax.set_title(
+                "Barometric Pressure", fontsize=10, fontweight="bold",
+                color=OCEAN_BLUE, loc="left",
+            )
+
+    # X-axis formatting on bottom panel
+    axes[-1].xaxis.set_major_formatter(date_fmt)
+    axes[-1].xaxis.set_major_locator(mdates.AutoDateLocator())
+
+    title = "Marine Conditions"
+    if station_name:
+        title = f"{station_name} — {title}"
+    fig.suptitle(title, fontsize=14, fontweight="bold", color=OCEAN_BLUE, y=1.01)
+    fig.tight_layout()
+
+    buf = io.BytesIO()
+    fig.savefig(buf, format="png", dpi=150, bbox_inches="tight", facecolor=BG_COLOR)
+    plt.close(fig)
+    buf.seek(0)
+    return buf.getvalue()
+
+
+def render_conditions_html(snapshot: dict, station_name: str = "") -> str:
+    """Render a multi-panel conditions dashboard as an interactive HTML string.
+
+    Args:
+        snapshot: Dict from marine_conditions_snapshot with data product keys.
+        station_name: Station name for the chart title.
+
+    Returns:
+        Complete HTML document string.
+    """
+    import plotly.graph_objects as go
+    from plotly.subplots import make_subplots
+
+    has_predictions = "predictions" in snapshot
+    has_water_level = "water_level" in snapshot
+    has_wind = "wind" in snapshot
+    has_air_temp = "air_temperature" in snapshot
+    has_water_temp = "water_temperature" in snapshot
+    has_pressure = "air_pressure" in snapshot
+
+    panel_titles = []
+    if has_predictions or has_water_level:
+        panel_titles.append("Tides")
+    if has_wind:
+        panel_titles.append("Wind (kn)")
+    if has_air_temp or has_water_temp:
+        panel_titles.append("Temperature (\u00b0F)")
+    if has_pressure:
+        panel_titles.append("Barometric Pressure (mb)")
+
+    if not panel_titles:
+        return "<html><body><p>No data available for visualization.</p></body></html>"
+
+    n = len(panel_titles)
+    fig = make_subplots(rows=n, cols=1, shared_xaxes=True, subplot_titles=panel_titles)
+
+    row = 1
+
+    # Tide panel
+    if has_predictions or has_water_level:
+        if has_predictions:
+            preds = snapshot["predictions"].get("predictions", [])
+            if preds:
+                from noaa_tides.charts.tides import _parse_predictions
+
+                p_times, p_values, markers = _parse_predictions(preds)
+                fig.add_trace(
+                    go.Scatter(
+                        x=p_times, y=p_values, mode="lines", name="Predicted",
+                        line={"color": OCEAN_BLUE, "width": 2},
+                    ),
+                    row=row, col=1,
+                )
+                highs = [m for m in markers if m["type"] == "H"]
+                lows = [m for m in markers if m["type"] == "L"]
+                if highs:
+                    fig.add_trace(
+                        go.Scatter(
+                            x=[m["time"] for m in highs],
+                            y=[m["value"] for m in highs],
+                            mode="markers", name="High",
+                            marker={"color": SAND, "size": 8, "symbol": "triangle-up"},
+                        ),
+                        row=row, col=1,
+                    )
+                if lows:
+                    fig.add_trace(
+                        go.Scatter(
+                            x=[m["time"] for m in lows],
+                            y=[m["value"] for m in lows],
+                            mode="markers", name="Low",
+                            marker={"color": CORAL, "size": 8, "symbol": "triangle-down"},
+                        ),
+                        row=row, col=1,
+                    )
+        if has_water_level:
+            obs_data = snapshot["water_level"].get("data", [])
+            if obs_data:
+                from noaa_tides.charts.tides import _parse_observed
+
+                o_times, o_values = _parse_observed(obs_data)
+                if o_times:
+                    fig.add_trace(
+                        go.Scatter(
+                            x=o_times, y=o_values, mode="lines", name="Observed",
+                            line={"color": TEAL, "width": 1.5, "dash": "dash"},
+                            opacity=0.8,
+                        ),
+                        row=row, col=1,
+                    )
+        row += 1
+
+    # Wind panel
+    if has_wind:
+        wind = _parse_wind(snapshot["wind"].get("data", []))
+        if wind["times"]:
+            fig.add_trace(
+                go.Scatter(
+                    x=wind["times"], y=wind["speeds"], mode="lines", name="Speed",
+                    line={"color": OCEAN_BLUE, "width": 1.5},
+                ),
+                row=row, col=1,
+            )
+            fig.add_trace(
+                go.Scatter(
+                    x=wind["times"], y=wind["gusts"], mode="lines", name="Gust",
+                    line={"color": CORAL, "width": 1, "dash": "dash"},
+                    opacity=0.6,
+                ),
+                row=row, col=1,
+            )
+        row += 1
+
+    # Temperature panel
+    if has_air_temp or has_water_temp:
+        if has_air_temp:
+            air_data = snapshot["air_temperature"].get("data", [])
+            at, av = _parse_time_series(air_data)
+            if at:
+                fig.add_trace(
+                    go.Scatter(
+                        x=at, y=av, mode="lines", name="Air Temp",
+                        line={"color": CORAL, "width": 1.5},
+                    ),
+                    row=row, col=1,
+                )
+        if has_water_temp:
+            water_data = snapshot["water_temperature"].get("data", [])
+            wt, wv = _parse_time_series(water_data)
+            if wt:
+                fig.add_trace(
+                    go.Scatter(
+                        x=wt, y=wv, mode="lines", name="Water Temp",
+                        line={"color": TEAL, "width": 1.5},
+                    ),
+                    row=row, col=1,
+                )
+        row += 1
+
+    # Pressure panel
+    if has_pressure:
+        press_data = snapshot["air_pressure"].get("data", [])
+        pt, pv = _parse_time_series(press_data)
+        if pt:
+            fig.add_trace(
+                go.Scatter(
+                    x=pt, y=pv, mode="lines", name="Pressure",
+                    line={"color": SLATE, "width": 1.5},
+                ),
+                row=row, col=1,
+            )
+
+    title = "Marine Conditions"
+    if station_name:
+        title = f"{station_name} &mdash; {title}"
+
+    fig.update_layout(
+        title={"text": title, "font": {"size": 16, "color": OCEAN_BLUE}},
+        plot_bgcolor=BG_COLOR,
+        paper_bgcolor=BG_COLOR,
+        font={"color": SLATE},
+        hovermode="x unified",
+        height=300 * n,
+        legend={"orientation": "h", "yanchor": "bottom", "y": 1.02, "xanchor": "right", "x": 1},
+        margin={"t": 80, "b": 40, "l": 60, "r": 20},
+    )
+
+    # Apply grid color to all axes
+    for i in range(1, n + 1):
+        fig.update_xaxes(gridcolor=GRID_COLOR, showgrid=True, row=i, col=1)
+        fig.update_yaxes(gridcolor=GRID_COLOR, showgrid=True, row=i, col=1)
+
+    return fig.to_html(include_plotlyjs="cdn", full_html=True)
diff --git a/src/noaa_tides/charts/tides.py b/src/noaa_tides/charts/tides.py
new file mode 100644
index 0000000..574df44
--- /dev/null
+++ b/src/noaa_tides/charts/tides.py
@@ -0,0 +1,223 @@
+"""Tide chart rendering — prediction curve with H/L markers and optional observed overlay."""
+
+import io
+from datetime import datetime
+
+from noaa_tides.charts import BG_COLOR, CORAL, GRID_COLOR, OCEAN_BLUE, SAND, SLATE, TEAL
+
+
+def _parse_predictions(predictions: list[dict]) -> tuple[list[datetime], list[float], list[dict]]:
+    """Extract timestamps, values, and H/L markers from prediction records."""
+    times = []
+    values = []
+    markers = []
+    for p in predictions:
+        dt = datetime.strptime(p["t"], "%Y-%m-%d %H:%M")
+        val = float(p["v"])
+        times.append(dt)
+        values.append(val)
+        if p.get("type") in ("H", "L"):
+            markers.append({"time": dt, "value": val, "type": p["type"]})
+    return times, values, markers
+
+
+def _parse_observed(data: list[dict]) -> tuple[list[datetime], list[float]]:
+    """Extract timestamps and values from observed water level records."""
+    times = []
+    values = []
+    for d in data:
+        if d.get("v") is None or d["v"] == "":
+            continue
+        dt = datetime.strptime(d["t"], "%Y-%m-%d %H:%M")
+        val = float(d["v"])
+        times.append(dt)
+        values.append(val)
+    return times, values
+
+
+def render_tide_chart_png(
+    predictions: list[dict],
+    observed: list[dict] | None = None,
+    station_name: str = "",
+) -> bytes:
+    """Render a tide prediction chart as PNG bytes.
+
+    Args:
+        predictions: List of prediction dicts with t, v, and optional type fields.
+        observed: Optional list of observed water level dicts with t, v fields.
+        station_name: Station name for the chart title.
+
+    Returns:
+        PNG image bytes.
+    """
+    import matplotlib
+
+    matplotlib.use("Agg")
+    import matplotlib.dates as mdates
+    import matplotlib.pyplot as plt
+
+    pred_times, pred_values, markers = _parse_predictions(predictions)
+
+    fig, ax = plt.subplots(figsize=(12, 5), facecolor=BG_COLOR)
+    ax.set_facecolor(BG_COLOR)
+
+    # Prediction line
+    ax.plot(pred_times, pred_values, color=OCEAN_BLUE, linewidth=2, label="Predicted", zorder=3)
+
+    # H/L markers
+    for m in markers:
+        is_high = m["type"] == "H"
+        color = SAND if is_high else CORAL
+        ax.plot(m["time"], m["value"], marker="o", color=color, markersize=8, zorder=4)
+        label = f'{m["type"]} {m["value"]:.1f}ft'
+        ax.annotate(
+            label,
+            (m["time"], m["value"]),
+            textcoords="offset points",
+            xytext=(0, 14 if is_high else -18),
+            fontsize=8,
+            fontweight="bold",
+            color=color,
+            ha="center",
+            zorder=5,
+        )
+
+    # Observed overlay
+    if observed:
+        obs_times, obs_values = _parse_observed(observed)
+        if obs_times:
+            ax.plot(
+                obs_times,
+                obs_values,
+                color=TEAL,
+                linewidth=1.5,
+                linestyle="--",
+                alpha=0.8,
+                label="Observed",
+                zorder=2,
+            )
+
+    # Zero reference line (MLLW datum)
+    ax.axhline(y=0, color=SLATE, linewidth=0.5, linestyle="-", alpha=0.4, zorder=1)
+
+    # Formatting
+    ax.xaxis.set_major_formatter(mdates.DateFormatter("%b %d\n%H:%M"))
+    ax.xaxis.set_major_locator(mdates.AutoDateLocator())
+    ax.set_ylabel("Water Level (ft, MLLW)", fontsize=10, color=SLATE)
+    ax.set_xlabel("")
+    ax.tick_params(colors=SLATE, labelsize=9)
+    ax.grid(True, alpha=0.3, color=GRID_COLOR, zorder=0)
+    ax.legend(loc="upper right", fontsize=9, framealpha=0.9)
+
+    title = "Tide Predictions"
+    if station_name:
+        title = f"{station_name} — {title}"
+    ax.set_title(title, fontsize=13, fontweight="bold", color=OCEAN_BLUE, pad=12)
+
+    fig.tight_layout()
+
+    buf = io.BytesIO()
+    fig.savefig(buf, format="png", dpi=150, bbox_inches="tight", facecolor=BG_COLOR)
+    plt.close(fig)
+    buf.seek(0)
+    return buf.getvalue()
+
+
+def render_tide_chart_html(
+    predictions: list[dict],
+    observed: list[dict] | None = None,
+    station_name: str = "",
+) -> str:
+    """Render a tide prediction chart as an interactive HTML string.
+
+    Args:
+        predictions: List of prediction dicts with t, v, and optional type fields.
+        observed: Optional list of observed water level dicts with t, v fields.
+        station_name: Station name for the chart title.
+
+    Returns:
+        Complete HTML document string.
+    """
+    import plotly.graph_objects as go
+
+    pred_times, pred_values, markers = _parse_predictions(predictions)
+
+    fig = go.Figure()
+
+    # Prediction line
+    fig.add_trace(
+        go.Scatter(
+            x=pred_times,
+            y=pred_values,
+            mode="lines",
+            name="Predicted",
+            line={"color": OCEAN_BLUE, "width": 2},
+        )
+    )
+
+    # H/L markers as separate traces
+    highs = [m for m in markers if m["type"] == "H"]
+    lows = [m for m in markers if m["type"] == "L"]
+
+    if highs:
+        fig.add_trace(
+            go.Scatter(
+                x=[m["time"] for m in highs],
+                y=[m["value"] for m in highs],
+                mode="markers+text",
+                name="High",
+                marker={"color": SAND, "size": 10, "symbol": "triangle-up"},
+                text=[f'H {m["value"]:.1f}ft' for m in highs],
+                textposition="top center",
+                textfont={"size": 10, "color": SAND},
+            )
+        )
+
+    if lows:
+        fig.add_trace(
+            go.Scatter(
+                x=[m["time"] for m in lows],
+                y=[m["value"] for m in lows],
+                mode="markers+text",
+                name="Low",
+                marker={"color": CORAL, "size": 10, "symbol": "triangle-down"},
+                text=[f'L {m["value"]:.1f}ft' for m in lows],
+                textposition="bottom center",
+                textfont={"size": 10, "color": CORAL},
+            )
+        )
+
+    # Observed overlay
+    if observed:
+        obs_times, obs_values = _parse_observed(observed)
+        if obs_times:
+            fig.add_trace(
+                go.Scatter(
+                    x=obs_times,
+                    y=obs_values,
+                    mode="lines",
+                    name="Observed",
+                    line={"color": TEAL, "width": 1.5, "dash": "dash"},
+                    opacity=0.8,
+                )
+            )
+
+    title = "Tide Predictions"
+    if station_name:
+        title = f"{station_name} &mdash; {title}"
+
+    fig.update_layout(
+        title={"text": title, "font": {"size": 16, "color": OCEAN_BLUE}},
+        xaxis_title="",
+        yaxis_title="Water Level (ft, MLLW)",
+        plot_bgcolor=BG_COLOR,
+        paper_bgcolor=BG_COLOR,
+        font={"color": SLATE},
+        hovermode="x unified",
+        legend={"orientation": "h", "yanchor": "bottom", "y": 1.02, "xanchor": "right", "x": 1},
+        xaxis={"gridcolor": GRID_COLOR, "showgrid": True},
+        yaxis={"gridcolor": GRID_COLOR, "showgrid": True, "zeroline": True},
+        margin={"t": 60, "b": 40, "l": 60, "r": 20},
+    )
+
+    return fig.to_html(include_plotlyjs="cdn", full_html=True)
diff --git a/src/noaa_tides/server.py b/src/noaa_tides/server.py
index b7683c2..155b09b 100644
--- a/src/noaa_tides/server.py
+++ b/src/noaa_tides/server.py
@@ -7,7 +7,7 @@ from fastmcp import FastMCP
 
 from noaa_tides import __version__, prompts, resources
 from noaa_tides.client import NOAAClient
-from noaa_tides.tools import conditions, meteorological, stations, tides
+from noaa_tides.tools import charts, conditions, meteorological, stations, tides
 
 
 @asynccontextmanager
@@ -49,6 +49,7 @@ stations.register(mcp)
 tides.register(mcp)
 meteorological.register(mcp)
 conditions.register(mcp)
+charts.register(mcp)
 
 # Register resources and prompts
 resources.register(mcp)
diff --git a/src/noaa_tides/tools/charts.py b/src/noaa_tides/tools/charts.py
new file mode 100644
index 0000000..5398df3
--- /dev/null
+++ b/src/noaa_tides/tools/charts.py
@@ -0,0 +1,181 @@
+"""Visualization tools — tide charts and conditions dashboards."""
+
+import asyncio
+from datetime import datetime, timezone
+from pathlib import Path
+from typing import Literal
+
+from fastmcp import Context, FastMCP
+from fastmcp.utilities.types import Image
+
+from noaa_tides.charts import check_deps
+from noaa_tides.client import NOAAClient
+
+
+def register(mcp: FastMCP) -> None:
+    @mcp.tool(tags={"visualization"})
+    async def visualize_tides(
+        ctx: Context,
+        station_id: str,
+        hours: int = 48,
+        include_observed: bool = True,
+        format: Literal["png", "html"] = "png",
+    ) -> Image | str:
+        """Generate a tide prediction chart with high/low markers.
+
+        Creates a visual chart of tide predictions showing the water level curve
+        with high (H) and low (L) tide markers. Optionally overlays observed
+        water levels as a dashed line for comparison.
+
+        PNG format returns an inline image. HTML format saves an interactive
+        chart to artifacts/charts/ and returns the file path.
+
+        Requires noaa-tides[viz] to be installed.
+        """
+        check_deps(format)
+        noaa: NOAAClient = ctx.lifespan_context["noaa_client"]
+
+        today = datetime.now(timezone.utc).strftime("%Y%m%d")
+
+        # Fetch predictions (6-minute interval for smooth curve) + hilo for markers
+        predictions_raw, hilo_raw = await asyncio.gather(
+            noaa.get_data(
+                station_id, product="predictions", begin_date=today,
+                hours=hours, interval="6",
+            ),
+            noaa.get_data(
+                station_id, product="predictions", begin_date=today,
+                hours=hours, interval="hilo",
+            ),
+        )
+
+        # Merge hilo type markers into the 6-minute data points
+        predictions = predictions_raw.get("predictions", [])
+        hilo_map = {}
+        for h in hilo_raw.get("predictions", []):
+            hilo_map[h["t"]] = h.get("type")
+
+        for p in predictions:
+            if p["t"] in hilo_map:
+                p["type"] = hilo_map[p["t"]]
+
+        # Fetch observed water levels if requested
+        observed = None
+        if include_observed:
+            try:
+                obs_raw = await noaa.get_data(
+                    station_id, product="water_level", hours=hours,
+                )
+                observed = obs_raw.get("data", [])
+            except Exception:
+                pass  # observed overlay is optional — skip on failure
+
+        # Look up station name
+        station_name = ""
+        try:
+            stations = await noaa.get_stations()
+            match = [s for s in stations if s.id == station_id]
+            if match:
+                station_name = match[0].name
+        except Exception:
+            pass
+
+        if format == "png":
+            from noaa_tides.charts.tides import render_tide_chart_png
+
+            png_bytes = render_tide_chart_png(predictions, observed, station_name)
+            return Image(data=png_bytes, format="image/png")
+        else:
+            from noaa_tides.charts.tides import render_tide_chart_html
+
+            html = render_tide_chart_html(predictions, observed, station_name)
+            path = _save_html(html, station_id, "tides")
+            return f"Interactive tide chart saved to: {path}"
+
+    @mcp.tool(tags={"visualization"})
+    async def visualize_conditions(
+        ctx: Context,
+        station_id: str,
+        hours: int = 24,
+        format: Literal["png", "html"] = "png",
+    ) -> Image | str:
+        """Generate a multi-panel marine conditions dashboard.
+
+        Creates a dashboard with up to 4 panels:
+        - Tide predictions with observed water level overlay
+        - Wind speed and gust
+        - Air and water temperature
+        - Barometric pressure with trend indicator
+
+        Products unavailable at a station are simply omitted from the dashboard.
+
+        PNG format returns an inline image. HTML format saves an interactive
+        chart to artifacts/charts/ and returns the file path.
+
+        Requires noaa-tides[viz] to be installed.
+        """
+        check_deps(format)
+        noaa: NOAAClient = ctx.lifespan_context["noaa_client"]
+
+        today = datetime.now(timezone.utc).strftime("%Y%m%d")
+
+        # Parallel fetch — same products as marine_conditions_snapshot
+        requests = {
+            "predictions": {
+                "product": "predictions", "interval": "hilo",
+                "begin_date": today, "hours": hours,
+            },
+            "water_level": {"product": "water_level", "hours": hours},
+            "water_temperature": {"product": "water_temperature", "hours": hours},
+            "air_temperature": {"product": "air_temperature", "hours": hours},
+            "wind": {"product": "wind", "hours": hours},
+            "air_pressure": {"product": "air_pressure", "hours": hours},
+        }
+
+        async def fetch(name: str, params: dict) -> tuple[str, dict | None]:
+            try:
+                data = await noaa.get_data(station_id, **params)
+                return name, data
+            except Exception:
+                return name, None
+
+        results = await asyncio.gather(
+            *[fetch(name, params) for name, params in requests.items()]
+        )
+
+        snapshot: dict = {"station_id": station_id}
+        for name, data in results:
+            if data is not None:
+                snapshot[name] = data
+
+        # Look up station name
+        station_name = ""
+        try:
+            stations = await noaa.get_stations()
+            match = [s for s in stations if s.id == station_id]
+            if match:
+                station_name = match[0].name
+        except Exception:
+            pass
+
+        if format == "png":
+            from noaa_tides.charts.conditions import render_conditions_png
+
+            png_bytes = render_conditions_png(snapshot, station_name)
+            return Image(data=png_bytes, format="image/png")
+        else:
+            from noaa_tides.charts.conditions import render_conditions_html
+
+            html = render_conditions_html(snapshot, station_name)
+            path = _save_html(html, station_id, "conditions")
+            return f"Interactive conditions dashboard saved to: {path}"
+
+
+def _save_html(html: str, station_id: str, chart_type: str) -> Path:
+    """Save HTML chart to artifacts/charts/ and return the path."""
+    timestamp = datetime.now(timezone.utc).strftime("%Y%m%d_%H%M%S")
+    out_dir = Path("artifacts/charts")
+    out_dir.mkdir(parents=True, exist_ok=True)
+    path = out_dir / f"{station_id}_{chart_type}_{timestamp}.html"
+    path.write_text(html, encoding="utf-8")
+    return path
diff --git a/tests/conftest.py b/tests/conftest.py
index a31c5f5..7542093 100644
--- a/tests/conftest.py
+++ b/tests/conftest.py
@@ -10,7 +10,7 @@ from fastmcp.utilities.tests import run_server_async
 
 from noaa_tides import prompts, resources
 from noaa_tides.client import NOAAClient
-from noaa_tides.tools import conditions, meteorological, stations, tides
+from noaa_tides.tools import charts, conditions, meteorological, stations, tides
 
 # Realistic station fixtures
 MOCK_STATIONS_RAW = [
@@ -140,6 +140,7 @@ def _build_test_server() -> FastMCP:
     tides.register(mcp)
     meteorological.register(mcp)
     conditions.register(mcp)
+    charts.register(mcp)
     resources.register(mcp)
     prompts.register(mcp)
     return mcp
diff --git a/tests/test_charts.py b/tests/test_charts.py
new file mode 100644
index 0000000..8b70a19
--- /dev/null
+++ b/tests/test_charts.py
@@ -0,0 +1,175 @@
+"""Tests for chart rendering and visualization tool registration."""
+
+import pytest
+from fastmcp import Client
+
+from noaa_tides.charts.conditions import render_conditions_html, render_conditions_png
+from noaa_tides.charts.tides import (
+    _parse_observed,
+    _parse_predictions,
+    render_tide_chart_html,
+    render_tide_chart_png,
+)
+
+# Mock data (matches conftest.py fixtures)
+MOCK_PREDICTIONS = {
+    "predictions": [
+        {"t": "2026-02-21 04:30", "v": "4.521", "type": "H"},
+        {"t": "2026-02-21 10:42", "v": "-0.123", "type": "L"},
+        {"t": "2026-02-21 16:55", "v": "5.012", "type": "H"},
+        {"t": "2026-02-21 23:08", "v": "0.234", "type": "L"},
+    ]
+}
+MOCK_WATER_LEVEL = {
+    "data": [
+        {"t": "2026-02-21 00:00", "v": "2.34", "s": "0.003", "f": "0,0,0,0", "q": "p"},
+        {"t": "2026-02-21 00:06", "v": "2.38", "s": "0.003", "f": "0,0,0,0", "q": "p"},
+    ]
+}
+MOCK_WIND = {
+    "data": [
+        {"t": "2026-02-21 00:00", "s": "12.5", "d": "225.00", "dr": "SW", "g": "18.2", "f": "0,0"}
+    ]
+}
+MOCK_AIR_TEMP = {"data": [{"t": "2026-02-21 00:00", "v": "42.3", "f": "0,0,0"}]}
+MOCK_WATER_TEMP = {"data": [{"t": "2026-02-21 00:00", "v": "38.7", "f": "0,0,0"}]}
+MOCK_PRESSURE = {"data": [{"t": "2026-02-21 00:00", "v": "1013.2", "f": "0,0,0"}]}
+
+
+# -- Parsing helpers --
+
+
+def test_parse_predictions():
+    preds = MOCK_PREDICTIONS["predictions"]
+    times, values, markers = _parse_predictions(preds)
+    assert len(times) == 4
+    assert len(values) == 4
+    assert len(markers) == 4
+    assert markers[0]["type"] == "H"
+    assert markers[1]["type"] == "L"
+    assert values[0] == pytest.approx(4.521)
+
+
+def test_parse_observed():
+    obs = MOCK_WATER_LEVEL["data"]
+    times, values = _parse_observed(obs)
+    assert len(times) == 2
+    assert values[0] == pytest.approx(2.34)
+
+
+def test_parse_observed_skips_blank_values():
+    data = [
+        {"t": "2026-02-21 00:00", "v": "2.34"},
+        {"t": "2026-02-21 00:06", "v": ""},
+        {"t": "2026-02-21 00:12", "v": None},
+    ]
+    times, values = _parse_observed(data)
+    assert len(times) == 1
+
+
+# -- Tide chart rendering --
+
+
+def test_tide_chart_png_returns_bytes():
+    preds = MOCK_PREDICTIONS["predictions"]
+    result = render_tide_chart_png(preds, station_name="Test Station")
+    assert isinstance(result, bytes)
+    assert len(result) > 0
+    # PNG magic bytes
+    assert result[:4] == b"\x89PNG"
+
+
+def test_tide_chart_png_with_observed():
+    preds = MOCK_PREDICTIONS["predictions"]
+    obs = MOCK_WATER_LEVEL["data"]
+    result = render_tide_chart_png(preds, observed=obs, station_name="Providence")
+    assert isinstance(result, bytes)
+    assert result[:4] == b"\x89PNG"
+
+
+def test_tide_chart_html_returns_string():
+    preds = MOCK_PREDICTIONS["predictions"]
+    result = render_tide_chart_html(preds, station_name="Test Station")
+    assert isinstance(result, str)
+    assert "<html>" in result.lower() or "<!doctype" in result.lower()
+    assert "plotly" in result.lower()
+
+
+def test_tide_chart_html_with_observed():
+    preds = MOCK_PREDICTIONS["predictions"]
+    obs = MOCK_WATER_LEVEL["data"]
+    result = render_tide_chart_html(preds, observed=obs, station_name="Providence")
+    assert isinstance(result, str)
+    assert "Observed" in result
+
+
+# -- Conditions dashboard rendering --
+
+
+def _build_snapshot(**overrides) -> dict:
+    """Build a snapshot dict from mock data."""
+    snapshot = {
+        "station_id": "8454000",
+        "predictions": MOCK_PREDICTIONS,
+        "water_level": MOCK_WATER_LEVEL,
+        "wind": MOCK_WIND,
+        "air_temperature": MOCK_AIR_TEMP,
+        "water_temperature": MOCK_WATER_TEMP,
+        "air_pressure": MOCK_PRESSURE,
+    }
+    snapshot.update(overrides)
+    return snapshot
+
+
+def test_conditions_png_returns_bytes():
+    snapshot = _build_snapshot()
+    result = render_conditions_png(snapshot, station_name="Providence")
+    assert isinstance(result, bytes)
+    assert result[:4] == b"\x89PNG"
+
+
+def test_conditions_png_partial_data():
+    """Dashboard should render even with missing products."""
+    snapshot = _build_snapshot()
+    del snapshot["wind"]
+    del snapshot["air_temperature"]
+    result = render_conditions_png(snapshot, station_name="Providence")
+    assert isinstance(result, bytes)
+    assert result[:4] == b"\x89PNG"
+
+
+def test_conditions_png_empty_snapshot():
+    """Dashboard with no data produces a placeholder image."""
+    result = render_conditions_png({"station_id": "8454000"})
+    assert isinstance(result, bytes)
+    assert result[:4] == b"\x89PNG"
+
+
+def test_conditions_html_returns_string():
+    snapshot = _build_snapshot()
+    result = render_conditions_html(snapshot, station_name="Providence")
+    assert isinstance(result, str)
+    assert "plotly" in result.lower()
+
+
+def test_conditions_html_empty_snapshot():
+    result = render_conditions_html({"station_id": "8454000"})
+    assert isinstance(result, str)
+    assert "No data available" in result
+
+
+# -- Tool registration --
+
+
+async def test_visualization_tools_registered(mcp_client: Client):
+    """The 2 new visualization tools should appear in the tool list."""
+    tools = await mcp_client.list_tools()
+    names = {t.name for t in tools}
+    assert "visualize_tides" in names
+    assert "visualize_conditions" in names
+
+
+async def test_total_tool_count(mcp_client: Client):
+    """Verify total tool count after adding visualization tools (7 + 2 = 9)."""
+    tools = await mcp_client.list_tools()
+    assert len(tools) == 9
diff --git a/tests/test_tools_stations.py b/tests/test_tools_stations.py
index 05ca74b..ba946c9 100644
--- a/tests/test_tools_stations.py
+++ b/tests/test_tools_stations.py
@@ -6,7 +6,7 @@ from fastmcp import Client
 
 
 async def test_tool_registration(mcp_client: Client):
-    """All 7 tools should be registered."""
+    """All 9 tools should be registered."""
     tools = await mcp_client.list_tools()
     tool_names = {t.name for t in tools}
     expected = {
@@ -17,6 +17,8 @@ async def test_tool_registration(mcp_client: Client):
         "get_observed_water_levels",
         "get_meteorological_data",
         "marine_conditions_snapshot",
+        "visualize_tides",
+        "visualize_conditions",
     }
     assert expected == tool_names
 
diff --git a/uv.lock b/uv.lock
index 28d6eda..4b12809 100644
--- a/uv.lock
+++ b/uv.lock
@@ -177,6 +177,72 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/d1/d6/3965ed04c63042e047cb6a3e6ed1a63a35087b6a609aa3a15ed8ac56c221/colorama-0.4.6-py2.py3-none-any.whl", hash = "sha256:4f1d9991f5acc0ca119f9d443620b77f9d6b33703e51011c16baf57afb285fc6", size = 25335, upload-time = "2022-10-25T02:36:20.889Z" },
 ]
 
+[[package]]
+name = "contourpy"
+version = "1.3.3"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "numpy" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/58/01/1253e6698a07380cd31a736d248a3f2a50a7c88779a1813da27503cadc2a/contourpy-1.3.3.tar.gz", hash = "sha256:083e12155b210502d0bca491432bb04d56dc3432f95a979b429f2848c3dbe880", size = 13466174, upload-time = "2025-07-26T12:03:12.549Z" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/be/45/adfee365d9ea3d853550b2e735f9d66366701c65db7855cd07621732ccfc/contourpy-1.3.3-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:b08a32ea2f8e42cf1d4be3169a98dd4be32bafe4f22b6c4cb4ba810fa9e5d2cb", size = 293419, upload-time = "2025-07-26T12:01:21.16Z" },
+    { url = "https://files.pythonhosted.org/packages/53/3e/405b59cfa13021a56bba395a6b3aca8cec012b45bf177b0eaf7a202cde2c/contourpy-1.3.3-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:556dba8fb6f5d8742f2923fe9457dbdd51e1049c4a43fd3986a0b14a1d815fc6", size = 273979, upload-time = "2025-07-26T12:01:22.448Z" },
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 name = "mcp"
 version = "1.26.0"
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 ]
 
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 name = "noaa-tides"
 version = "2026.2.21"
@@ -576,23 +827,97 @@ dependencies = [
     { name = "fastmcp" },
 ]
 
+[package.optional-dependencies]
+viz = [
+    { name = "matplotlib" },
+    { name = "plotly" },
+]
+
 [package.dev-dependencies]
 dev = [
+    { name = "noaa-tides", extra = ["viz"] },
     { name = "pytest" },
     { name = "pytest-asyncio" },
     { name = "ruff" },
 ]
 
 [package.metadata]
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+requires-dist = [
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+    { name = "matplotlib", marker = "extra == 'viz'", specifier = ">=3.8" },
+    { name = "plotly", marker = "extra == 'viz'", specifier = ">=5.18" },
+]
+provides-extras = ["viz"]
 
 [package.metadata.requires-dev]
 dev = [
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     { name = "pytest", specifier = ">=8" },
     { name = "pytest-asyncio", specifier = ">=0.24" },
     { name = "ruff", specifier = ">=0.9" },
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