Skip to main content
Glama
javerthl

ServiceNow MCP Server

by javerthl

create_story

Create new stories in ServiceNow with required details like short description and acceptance criteria, plus optional fields for state, assignment, and project tracking.

Instructions

Create a new story in ServiceNow

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
acceptance_criteriaYesAcceptance criteria for the story
assigned_toNoUser assigned to the story
assignment_groupNoGroup assigned to the story
descriptionNoDetailed description of the story
epicNoEpic that the story belongs to. It requires the System ID of the epic.
projectNoProject that the story belongs to. It requires the System ID of the project.
short_descriptionYesShort description of the story
stateNoState of story (-6 is Draft,-7 is Ready for Testing,-8 is Testing,1 is Ready, 2 is Work in progress, 3 is Complete, 4 is Cancelled)
story_pointsNoPoints value for the story
work_notesNoWork notes to add to the story. Used for adding notes and comments to a story

Implementation Reference

  • The main handler function that implements the create_story tool logic by validating parameters and making a POST request to the ServiceNow rm_story table API.
    def create_story(
        auth_manager: AuthManager,
        server_config: ServerConfig,
        params: Dict[str, Any],
    ) -> Dict[str, Any]:
        """
        Create a new story in ServiceNow.
    
        Args:
            auth_manager: The authentication manager.
            server_config: The server configuration.
            params: The parameters for creating the story.
    
        Returns:
            The created story.
        """
    
        # Unwrap and validate parameters
        result = _unwrap_and_validate_params(
            params, 
            CreateStoryParams, 
            required_fields=["short_description", "acceptance_criteria"]
        )
        
        if not result["success"]:
            return result
        
        validated_params = result["params"]
        
        # Prepare the request data
        data = {
            "short_description": validated_params.short_description,
            "acceptance_criteria": validated_params.acceptance_criteria,
        }
           
        # Add optional fields if provided
        if validated_params.description:
            data["description"] = validated_params.description
        if validated_params.state:
            data["state"] = validated_params.state
        if validated_params.assignment_group:
            data["assignment_group"] = validated_params.assignment_group
        if validated_params.story_points:
            data["story_points"] = validated_params.story_points
        if validated_params.assigned_to:
            data["assigned_to"] = validated_params.assigned_to
        if validated_params.epic:
            data["epic"] = validated_params.epic
        if validated_params.project:
            data["project"] = validated_params.project
        if validated_params.work_notes:
            data["work_notes"] = validated_params.work_notes
        
        # 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/rm_story"
        
        try:
            response = requests.post(url, json=data, headers=headers)
            response.raise_for_status()
            
            result = response.json()
            
            return {
                "success": True,
                "message": "Story created successfully",
                "story": result["result"],
            }
        except requests.exceptions.RequestException as e:
            logger.error(f"Error creating story: {e}")
            return {
                "success": False,
                "message": f"Error creating story: {str(e)}",
            }
  • Pydantic BaseModel defining the input schema/parameters for the create_story tool.
    class CreateStoryParams(BaseModel):
        """Parameters for creating a story."""
    
        short_description: str = Field(..., description="Short description of the story")
        acceptance_criteria: str = Field(..., description="Acceptance criteria for the story")
        description: Optional[str] = Field(None, description="Detailed description of the story")
        state: Optional[str] = Field(None, description="State of story (-6 is Draft,-7 is Ready for Testing,-8 is Testing,1 is Ready, 2 is Work in progress, 3 is Complete, 4 is Cancelled)")
        assignment_group: Optional[str] = Field(None, description="Group assigned to the story")
        story_points: Optional[int] = Field(10, description="Points value for the story")
        assigned_to: Optional[str] = Field(None, description="User assigned to the story")
        epic: Optional[str] = Field(None, description="Epic that the story belongs to. It requires the System ID of the epic.")
        project: Optional[str] = Field(None, description="Project that the story belongs to. It requires the System ID of the project.")
        work_notes: Optional[str] = Field(None, description="Work notes to add to the story. Used for adding notes and comments to a story")
  • The registration of the 'create_story' tool in the central tool_definitions dictionary used by the MCP server, linking the handler function, input schema, description, and serialization method.
    "create_story": (
        create_story_tool,
        CreateStoryParams,
        str,
        "Create a new story in ServiceNow",
        "str",
    ),
  • Import of the create_story handler into the tools package __init__.py, exposing it for use in other modules like tool_utils.py.
    from servicenow_mcp.tools.story_tools import (
        create_story,
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 it creates a story but doesn't mention required permissions, whether the operation is idempotent, what happens on failure, or the format of the response. For a mutation tool with zero annotation coverage, this is a significant gap.

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 a single, efficient sentence with zero wasted words. It's front-loaded with the core purpose and appropriately sized for a tool with comprehensive schema documentation.

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 mutation tool with 10 parameters, no annotations, and no output schema, the description is inadequate. It doesn't explain what happens after creation (e.g., returns a story ID), error conditions, or system behavior. The agent lacks crucial context for proper tool invocation.

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?

Schema description coverage is 100%, so the schema fully documents all 10 parameters. The description adds no parameter-specific information beyond what's in the schema, such as explaining relationships between fields or providing examples. Baseline 3 is appropriate when the schema does all the work.

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 action ('Create') and resource ('new story in ServiceNow'), making the purpose unambiguous. However, it doesn't differentiate this tool from sibling tools like 'create_epic' or 'create_incident' beyond the resource type, missing explicit sibling differentiation.

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 'create_epic' or 'update_story'. There's no mention of prerequisites, context, or exclusions, leaving the agent to infer usage from the tool name alone.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/javerthl/servicenow-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server