pl_stacked_violin

Instructions

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "pl_stacked_violin"
  }
}

Implementation Reference

• src/scmcp/tool/pl.py:179-216 (handler)

  Generic handler function that executes all 'pl_' tools, including 'pl_stacked_violin', by mapping the tool name to sc.pl.stacked_violin and calling it with input arguments after validation.

  def run_pl_func(ads, func, arguments):
      """
      Execute a Scanpy plotting function with the given arguments.
      
      Parameters
      ----------
      adata : AnnData
          Annotated data matrix.
      func : str
          Name of the plotting function to execute.
      arguments : dict
          Arguments to pass to the plotting function.
          
      Returns
      -------
      The result of the plotting function.
      """
      adata = ads.adata_dic[ads.active]
      if func not in pl_func:
          raise ValueError(f"Unsupported function: {func}")
  
      run_func = pl_func[func]
      parameters = inspect.signature(run_func).parameters
      kwargs = {k: arguments.get(k) for k in parameters if k in arguments}    
  
      if "title" not in parameters:
          kwargs.pop("title", False)    
      kwargs.pop("return_fig", True)
      kwargs["show"] = False
      kwargs["save"] = ".png"
      try:
          fig = run_func(adata, **kwargs)
          fig_path = set_fig_path(func, **kwargs)
          add_op_log(adata, run_func, kwargs)
          return fig_path 
      except Exception as e:
          raise e
      return fig_path

• src/scmcp/schema/pl.py:646-686 (schema)

  Pydantic model defining the input schema and validation for the pl_stacked_violin tool.

  class StackedViolinModel(BaseStatPlotModel):
      """Input schema for the stacked_violin plotting tool."""
      
      stripplot: bool = Field(
          default=True,
          description="Add a stripplot on top of the violin plot."
      )
      
      jitter: Union[float, bool] = Field(
          default=True,
          description="Add jitter to the stripplot (only when stripplot is True)."
      )
      
      size: int = Field(
          default=1,
          description="Size of the jitter points.",
          gt=0
      )
      
      order: Optional[List[str]] = Field(
          default=None,
          description="Order in which to show the categories."
      )
      
      scale: Literal['area', 'count', 'width'] = Field(
          default='width',
          description="The method used to scale the width of each violin."
      )
      
      swap_axes: bool = Field(
          default=False,
          description="Swap axes such that observations are on the x-axis."
      )
      
      @field_validator('size')
      def validate_size(cls, v: int) -> int:
          """Validate size is positive"""
          if v <= 0:
              raise ValueError("size must be a positive integer")
          return v

• src/scmcp/tool/pl.py:35-39 (registration)

  Creates and configures the MCP Tool object for 'pl_stacked_violin' with schema reference.

  pl_stacked_violin = types.Tool(
      name="pl_stacked_violin",
      description="Plot stacked violin plots. Makes a compact image composed of individual violin plots stacked on top of each other.",
      inputSchema=StackedViolinModel.model_json_schema(),
  )

• src/scmcp/tool/pl.py:121-138 (registration)

  Maps the tool name 'pl_stacked_violin' to the underlying scanpy function sc.pl.stacked_violin for execution.

  pl_func = {
      "pl_pca": sc.pl.pca,
      "pl_embedding": sc.pl.embedding,  # Add the new embedding function
      "diffmap": sc.pl.diffmap,
      "pl_violin": sc.pl.violin,
      "pl_stacked_violin": sc.pl.stacked_violin,
      "pl_heatmap": sc.pl.heatmap,
      "pl_dotplot": sc.pl.dotplot,
      "pl_matrixplot": sc.pl.matrixplot,
      "pl_tracksplot": sc.pl.tracksplot,
      "pl_scatter": sc.pl.scatter,
      "embedding_density": sc.pl.embedding_density,
      "rank_genes_groups": sc.pl.rank_genes_groups,
      "pl_rank_genes_groups_dotplot": sc.pl.rank_genes_groups_dotplot,  # Add function mapping
      "pl_clustermap": sc.pl.clustermap,
      "pl_highly_variable_genes": sc.pl.highly_variable_genes,
      "pl_pca_variance_ratio": sc.pl.pca_variance_ratio,
  }

• src/scmcp/tool/pl.py:141-159 (registration)

  Registers the pl_stacked_violin Tool object in the pl_tools dictionary, which is exposed via server.list_tools().

  pl_tools = {
      "pl_pca": pl_pca_tool,
      "pl_embedding": pl_embedding,  # Add the new embedding tool
      # "diffmap": diffmap,
      "pl_violin": pl_violin,
      "pl_stacked_violin": pl_stacked_violin,
      "pl_heatmap": pl_heatmap,
      "pl_dotplot": pl_dotplot,
      "pl_matrixplot": pl_matrixplot,
      "pl_tracksplot": pl_tracksplot,
      "pl_scatter": pl_scatter,
      # "embedding_density": embedding_density,
      # "spatial": spatial,
      # "rank_genes_groups": rank_genes_groups,
      "pl_rank_genes_groups_dotplot": pl_rank_genes_groups_dotplot,  # Add tool mapping
      # "pl_clustermap": pl_clustermap,
      "pl_highly_variable_genes": pl_highly_variable_genes,
      "pl_pca_variance_ratio": pl_pca_variance_ratio,
  }