Fermat MCP

Instructions

Implementation Reference

• fmcp/mpl_mcp/core/stem_chart.py:8-136 (handler)

  The main handler function `plot_stem` that generates stem plots using matplotlib's stem function, supports multiple series, vertical/horizontal orientation, and returns a PNG image.

  def plot_stem(
      x_data: Union[List[Union[float, int]], List[List[Union[float, int]]]],
      y_data: Union[List[Union[float, int]], List[List[Union[float, int]]]],
      labels: Optional[Union[str, List[str]]] = None,
      title: str = "",
      xlabel: str = "",
      ylabel: str = "",
      colors: Union[str, List[str]] = "blue",
      linefmt: str = "-",
      markerfmt: str = "o",
      basefmt: str = "k-",
      bottom: float = 0.0,
      orientation: str = "vertical",  # "vertical" or "horizontal"
      dpi: int = 200,
      figsize: Optional[List[Union[int, float]]] = None,
      grid: bool = True,
      legend: bool = False,
  ) -> Image:
      """
      Create a stem plot (vertical or horizontal) with customizable appearance.
  
      Args:
          x_data: X-axis data points (1D array-like)
          y_data: Y-axis data points (1D or 2D array-like for multiple series)
          labels: Label or list of labels for the data series
          title: Plot title
          xlabel: Label for the x-axis
          ylabel: Label for the y-axis
          colors: Color or list of colors for the stems and markers
          linefmt: Line style for the stems (default: "-" for solid line)
          markerfmt: Marker style for the points (default: "o" for circles)
          basefmt: Format of the baseline (default: "k-" for black line)
          bottom: Position of the baseline (default: 0.0)
          orientation: "vertical" or "horizontal" (default: "vertical")
          dpi: Output image resolution (dots per inch, default: 200)
          figsize: Figure size as (width, height) in inches.
          grid: Whether to show grid lines (default: True)
          legend: Whether to show legend (default: False)
  
      Returns:
          FastMCP Image object with the plotted stem chart
      """
      # Convert inputs to numpy arrays with explicit float type
      x = np.asarray(x_data, dtype=float)
      y = np.asarray(y_data, dtype=float)
  
      # Handle 1D y_data case by adding an extra dimension
      if y.ndim == 1:
          y = y.reshape(1, -1)
  
      # Ensure x matches the number of data points in y
      if x.ndim == 1 and len(x) != y.shape[1]:
          x = np.tile(x, (y.shape[0], 1))
  
      # Handle labels — normalize to a list
      if labels is None:
          labels_list: List[str] = [""] * y.shape[0]
      elif isinstance(labels, str):
          labels_list = [labels]
      else:
          labels_list = list(labels)
  
      # Handle colors — normalize to a list
      if isinstance(colors, str):
          colors_list = [colors] * y.shape[0]
      else:
          colors_list = list(colors)
  
      # Create figure with specified size using OO interface
      # Normalize figsize
      if figsize and len(figsize) >= 2:
          figsize_vals = (float(figsize[0]), float(figsize[1]))
      else:
          figsize_vals = (6.0, 4.0)
  
      fig, ax = plt.subplots(figsize=figsize_vals, dpi=dpi)
  
      # Create the stem plot for each series
      # Create the stem plot for each series
      for i in range(y.shape[0]):
          current_label = labels_list[i] if i < len(labels_list) else f"Series {i+1}"
          current_color = colors_list[i % len(colors_list)]
  
          # Create the stem plot
          if orientation == "vertical":
              markerline, stemlines, baseline = ax.stem(
                  x[i] if x.ndim > 1 else x,
                  y[i],
                  linefmt=linefmt,
                  markerfmt=markerfmt,
                  basefmt=basefmt,
                  bottom=bottom,
                  label=current_label,
              )
          else:  # horizontal
              markerline, stemlines, baseline = ax.stem(
                  y[i],
                  x[i] if x.ndim > 1 else x,
                  linefmt=linefmt,
                  markerfmt=markerfmt,
                  basefmt=basefmt,
                  bottom=bottom,
                  label=current_label,
                  orientation="horizontal",
              )
  
          # Set the color for this series
          plt.setp(stemlines, "color", current_color)
          plt.setp(markerline, "color", current_color)
          plt.setp(baseline, "color", "black")
  
      # Customize the plot
      ax.set_title(title)
      ax.set_xlabel(xlabel if orientation == "vertical" else ylabel)
      ax.set_ylabel(ylabel if orientation == "vertical" else xlabel)
  
      if grid:
          ax.grid(True, linestyle="--", alpha=0.7)
  
      if legend and any(labels_list):
          ax.legend()
  
      # Save the plot to a buffer and close the figure
      buf = io.BytesIO()
      fig.savefig(buf, format="png", dpi=dpi, bbox_inches="tight")
      plt.close(fig)
      buf.seek(0)
  
      return Image(data=buf.read(), format="png")

• fmcp/mpl_mcp/server.py:22-22 (registration)

  Registers the `plot_stem` function as an MCP tool under the name `mpl_mcp_plot_stem` using FastMCP's tool decorator.

  mpl_mcp.tool(plot_stem, description="Plots stem chart of given datavalues")

• fmcp/mpl_mcp/core/stem_chart.py:8-25 (schema)

  The function signature with type annotations defines the input schema and output type for the tool.

  def plot_stem(
      x_data: Union[List[Union[float, int]], List[List[Union[float, int]]]],
      y_data: Union[List[Union[float, int]], List[List[Union[float, int]]]],
      labels: Optional[Union[str, List[str]]] = None,
      title: str = "",
      xlabel: str = "",
      ylabel: str = "",
      colors: Union[str, List[str]] = "blue",
      linefmt: str = "-",
      markerfmt: str = "o",
      basefmt: str = "k-",
      bottom: float = 0.0,
      orientation: str = "vertical",  # "vertical" or "horizontal"
      dpi: int = 200,
      figsize: Optional[List[Union[int, float]]] = None,
      grid: bool = True,
      legend: bool = False,
  ) -> Image: