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javerthl

ServiceNow MCP Server

by javerthl

update_catalog_item_variable

Modify catalog item variable properties such as label, mandatory status, help text, default value, description, display order, and validation rules in ServiceNow.

Instructions

Update a catalog item variable

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
default_valueNoDefault value for the variable
descriptionNoDescription of the variable
help_textNoHelp text to display with the variable
labelNoThe display label for the variable
mandatoryNoWhether the variable is required
maxNoMaximum value for numeric fields
max_lengthNoMaximum length for string fields
minNoMinimum value for numeric fields
orderNoDisplay order of the variable
reference_qualifierNoFor reference fields, the query to filter reference options
variable_idYesThe sys_id of the variable to update

Implementation Reference

  • The main handler function that implements the logic for updating a catalog item variable using ServiceNow REST API PATCH request to item_option_new table.
    def update_catalog_item_variable(
        config: ServerConfig,
        auth_manager: AuthManager,
        params: UpdateCatalogItemVariableParams,
    ) -> CatalogItemVariableResponse:
        """
        Update an existing variable (form field) for a catalog item.
    
        Args:
            config: Server configuration.
            auth_manager: Authentication manager.
            params: Parameters for updating a catalog item variable.
    
        Returns:
            Response with information about the updated variable.
        """
        api_url = f"{config.instance_url}/api/now/table/item_option_new/{params.variable_id}"
    
        # Build request data with only parameters that are provided
        data = {}
        
        if params.label is not None:
            data["question_text"] = params.label
        if params.mandatory is not None:
            data["mandatory"] = str(params.mandatory).lower()  # ServiceNow expects "true"/"false" strings
        if params.help_text is not None:
            data["help_text"] = params.help_text
        if params.default_value is not None:
            data["default_value"] = params.default_value
        if params.description is not None:
            data["description"] = params.description
        if params.order is not None:
            data["order"] = params.order
        if params.reference_qualifier is not None:
            data["reference_qual"] = params.reference_qualifier
        if params.max_length is not None:
            data["max_length"] = params.max_length
        if params.min is not None:
            data["min"] = params.min
        if params.max is not None:
            data["max"] = params.max
    
        # If no fields to update, return early
        if not data:
            return CatalogItemVariableResponse(
                success=False,
                message="No update parameters provided",
            )
    
        # Make request
        try:
            response = requests.patch(
                api_url,
                json=data,
                headers=auth_manager.get_headers(),
                timeout=config.timeout,
            )
            response.raise_for_status()
    
            result = response.json().get("result", {})
    
            return CatalogItemVariableResponse(
                success=True,
                message="Catalog item variable updated successfully",
                variable_id=params.variable_id,
                details=result,
            )
    
        except requests.RequestException as e:
            logger.error(f"Failed to update catalog item variable: {e}")
            return CatalogItemVariableResponse(
                success=False,
                message=f"Failed to update catalog item variable: {str(e)}",
            ) 
  • Pydantic model defining the input parameters for the update_catalog_item_variable tool, including validation and descriptions.
    class UpdateCatalogItemVariableParams(BaseModel):
        """Parameters for updating a catalog item variable."""
    
        variable_id: str = Field(..., description="The sys_id of the variable to update")
        label: Optional[str] = Field(None, description="The display label for the variable")
        mandatory: Optional[bool] = Field(None, description="Whether the variable is required")
        help_text: Optional[str] = Field(None, description="Help text to display with the variable")
        default_value: Optional[str] = Field(None, description="Default value for the variable")
        description: Optional[str] = Field(None, description="Description of the variable")
        order: Optional[int] = Field(None, description="Display order of the variable")
        reference_qualifier: Optional[str] = Field(None, description="For reference fields, the query to filter reference options")
        max_length: Optional[int] = Field(None, description="Maximum length for string fields")
        min: Optional[int] = Field(None, description="Minimum value for numeric fields")
        max: Optional[int] = Field(None, description="Maximum value for numeric fields")
  • Registration of the tool in the central tool_definitions dictionary, mapping the tool name to its implementation, params schema, description, and serialization method.
    "update_catalog_item_variable": (
        update_catalog_item_variable_tool,
        UpdateCatalogItemVariableParams,
        Dict[str, Any],  # Expects dict
        "Update a catalog item variable",
        "dict",  # Tool returns Pydantic model
    ),
  • Import of the update_catalog_item_variable function into the tools package __init__.py, making it available for export in __all__.
    from servicenow_mcp.tools.catalog_variables import (
        create_catalog_item_variable,
        list_catalog_item_variables,
        update_catalog_item_variable,
  • Imports and aliasing of the function and params from catalog_variables.py for use in tool registration.
    from servicenow_mcp.tools.catalog_variables import (
        CreateCatalogItemVariableParams,
        ListCatalogItemVariablesParams,
        UpdateCatalogItemVariableParams,
    )
    from servicenow_mcp.tools.catalog_variables import (
        create_catalog_item_variable as create_catalog_item_variable_tool,
    )
    from servicenow_mcp.tools.catalog_variables import (
        list_catalog_item_variables as list_catalog_item_variables_tool,
    )
    from servicenow_mcp.tools.catalog_variables import (
        update_catalog_item_variable as update_catalog_item_variable_tool,
    )
Behavior1/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden of behavioral disclosure. The description only states 'Update a catalog item variable' without explaining what 'update' entails—whether it's a partial or full update, if it requires specific permissions, what happens to unspecified fields, whether changes are reversible, or what the response looks like. For a mutation tool with zero annotation coverage, this is a significant gap in behavioral transparency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely concise with just four words: 'Update a catalog item variable'. It's front-loaded and wastes no words, though this brevity comes at the cost of completeness. Every word serves a purpose, making it efficient in structure despite its informational shortcomings.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity (11 parameters, mutation operation) and lack of annotations and output schema, the description is incomplete. It doesn't explain the tool's behavior, return values, or usage context. While the schema covers parameters well, the description fails to provide necessary context for a mutation tool, especially with no output schema to clarify results.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema description coverage is 100%, with all 11 parameters well-documented in the input schema (e.g., 'default_value', 'description', 'help_text', 'variable_id'). The description adds no additional parameter semantics beyond what's already in the schema. According to the rules, when schema coverage is high (>80%), the baseline score is 3 even with no param info in the description, which applies here.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose2/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description 'Update a catalog item variable' is a tautology that essentially restates the tool name 'update_catalog_item_variable'. It doesn't specify what aspect of the variable gets updated (e.g., metadata, constraints, values) or what 'catalog item variable' means in this context. While it includes the verb 'update' and resource 'catalog item variable', it lacks specificity about scope or purpose beyond the obvious.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines1/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. Given the sibling tools include 'create_catalog_item_variable' and 'list_catalog_item_variables', there's no indication of when to use update versus create, or whether this is for modifying existing variables versus other operations. There are no prerequisites, exclusions, or contextual hints provided.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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