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ServiceNow MCP Server

create_change_request

Generate a change request in ServiceNow to manage and track changes effectively. Define details like type, description, impact, risk, and dates for streamlined approval and execution.

Instructions

Create a new change request in ServiceNow

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
paramsYes

Implementation Reference

  • The core handler function that executes the create_change_request tool. It validates input parameters using CreateChangeRequestParams, prepares the data, makes a POST request to ServiceNow's change_request table API, and returns the result.
    def create_change_request(
        auth_manager: AuthManager,
        server_config: ServerConfig,
        params: Dict[str, Any],
    ) -> Dict[str, Any]:
        """
        Create a new change request in ServiceNow.
    
        Args:
            auth_manager: The authentication manager.
            server_config: The server configuration.
            params: The parameters for creating the change request.
    
        Returns:
            The created change request.
        """
        # Unwrap and validate parameters
        result = _unwrap_and_validate_params(
            params, 
            CreateChangeRequestParams, 
            required_fields=["short_description", "type"]
        )
        
        if not result["success"]:
            return result
        
        validated_params = result["params"]
        
        # Prepare the request data
        data = {
            "short_description": validated_params.short_description,
            "type": validated_params.type,
        }
        
        # Add optional fields if provided
        if validated_params.description:
            data["description"] = validated_params.description
        if validated_params.risk:
            data["risk"] = validated_params.risk
        if validated_params.impact:
            data["impact"] = validated_params.impact
        if validated_params.category:
            data["category"] = validated_params.category
        if validated_params.requested_by:
            data["requested_by"] = validated_params.requested_by
        if validated_params.assignment_group:
            data["assignment_group"] = validated_params.assignment_group
        if validated_params.start_date:
            data["start_date"] = validated_params.start_date
        if validated_params.end_date:
            data["end_date"] = validated_params.end_date
        
        # Get the instance URL
        instance_url = _get_instance_url(auth_manager, server_config)
        if not instance_url:
            return {
                "success": False,
                "message": "Cannot find instance_url in either server_config or auth_manager",
            }
        
        # Get the headers
        headers = _get_headers(auth_manager, server_config)
        if not headers:
            return {
                "success": False,
                "message": "Cannot find get_headers method in either auth_manager or server_config",
            }
        
        # Add Content-Type header
        headers["Content-Type"] = "application/json"
        
        # Make the API request
        url = f"{instance_url}/api/now/table/change_request"
        
        try:
            response = requests.post(url, json=data, headers=headers)
            response.raise_for_status()
            
            result = response.json()
            
            return {
                "success": True,
                "message": "Change request created successfully",
                "change_request": result["result"],
            }
        except requests.exceptions.RequestException as e:
            logger.error(f"Error creating change request: {e}")
            return {
                "success": False,
                "message": f"Error creating change request: {str(e)}",
            }
  • Pydantic BaseModel defining the input schema for the create_change_request tool, including required fields like short_description and type, and optional fields like description, risk, etc.
    class CreateChangeRequestParams(BaseModel):
        """Parameters for creating a change request."""
    
        short_description: str = Field(..., description="Short description of the change request")
        description: Optional[str] = Field(None, description="Detailed description of the change request")
        type: str = Field(..., description="Type of change (normal, standard, emergency)")
        risk: Optional[str] = Field(None, description="Risk level of the change")
        impact: Optional[str] = Field(None, description="Impact of the change")
        category: Optional[str] = Field(None, description="Category of the change")
        requested_by: Optional[str] = Field(None, description="User who requested the change")
        assignment_group: Optional[str] = Field(None, description="Group assigned to the change")
        start_date: Optional[str] = Field(None, description="Planned start date (YYYY-MM-DD HH:MM:SS)")
        end_date: Optional[str] = Field(None, description="Planned end date (YYYY-MM-DD HH:MM:SS)")
  • Tool registration in get_tool_definitions() dictionary, mapping the tool name to its handler function (aliased as create_change_request_tool), input schema, return type, description, and serialization method.
    "create_change_request": (
        create_change_request_tool,
        CreateChangeRequestParams,
        str,
        "Create a new change request in ServiceNow",
        "str",
    ),
  • Helper function used by the handler to unwrap, validate required fields, and parse input parameters against the Pydantic schema.
    def _unwrap_and_validate_params(params: Any, model_class: Type[T], required_fields: List[str] = None) -> Dict[str, Any]:
        """
        Helper function to unwrap and validate parameters.
        
        Args:
            params: The parameters to unwrap and validate.
            model_class: The Pydantic model class to validate against.
            required_fields: List of required field names.
            
        Returns:
            A tuple of (success, result) where result is either the validated parameters or an error message.
        """
        # Handle case where params might be wrapped in another dictionary
        if isinstance(params, dict) and len(params) == 1 and "params" in params and isinstance(params["params"], dict):
            logger.warning("Detected params wrapped in a 'params' key. Unwrapping...")
            params = params["params"]
        
        # Handle case where params might be a Pydantic model object
        if not isinstance(params, dict):
            try:
                # Try to convert to dict if it's a Pydantic model
                logger.warning("Params is not a dictionary. Attempting to convert...")
                params = params.dict() if hasattr(params, "dict") else dict(params)
            except Exception as e:
                logger.error(f"Failed to convert params to dictionary: {e}")
                return {
                    "success": False,
                    "message": f"Invalid parameters format. Expected a dictionary, got {type(params).__name__}",
                }
        
        # Validate required parameters are present
        if required_fields:
            for field in required_fields:
                if field not in params:
                    return {
                        "success": False,
                        "message": f"Missing required parameter '{field}'",
                    }
        
        try:
            # Validate parameters against the model
            validated_params = model_class(**params)
            return {
                "success": True,
                "params": validated_params,
            }
        except Exception as e:
            logger.error(f"Error validating parameters: {e}")
            return {
                "success": False,
                "message": f"Error validating parameters: {str(e)}",
            }
Behavior2/5

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

With no annotations provided, the description carries full burden for behavioral disclosure. It states this is a creation operation but provides no information about permissions required, whether this triggers workflows or notifications, what happens on success/failure, or any side effects. The description doesn't compensate for the lack of annotations.

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 at just 7 words, front-loading the essential action and resource. There's no wasted language or unnecessary elaboration, making it efficient for an agent to parse.

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?

For a creation tool with 10 parameters, 0% schema description coverage, no annotations, and no output schema, this description is severely inadequate. It doesn't explain what constitutes a valid change request, what happens after creation, or provide any context about the ServiceNow change management process.

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

Parameters1/5

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

The schema description coverage is 0%, meaning none of the 10 parameters have descriptions in the schema. The tool description provides absolutely no information about parameters, not even mentioning the required 'short_description' and 'type' fields or explaining what a change request consists of.

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

Purpose4/5

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

The description clearly states the verb ('Create') and resource ('a new change request in ServiceNow'), making the purpose immediately understandable. However, it doesn't differentiate this tool from its sibling 'update_change_request' or explain what distinguishes creating from updating a change request.

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

Usage Guidelines2/5

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 like 'update_change_request' or 'list_change_requests'. There's no mention of prerequisites, appropriate contexts, or when this tool should be avoided in favor of other options.

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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