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JLKmach

ServiceNow MCP Server

by JLKmach

list_scrum_tasks

Retrieve and filter scrum tasks from ServiceNow to manage agile workflows, track progress, and organize team assignments with customizable parameters.

Instructions

List scrum tasks from ServiceNow

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum number of records to return
offsetNoOffset to start from
stateNoFilter by state
assignment_groupNoFilter by assignment group
timeframeNoFilter by timeframe (upcoming, in-progress, completed)
queryNoAdditional query string

Implementation Reference

  • The handler function implementing the core logic for the 'list_scrum_tasks' tool. It validates parameters, builds a ServiceNow API query based on filters like state, assignment_group, timeframe, and query, then fetches and returns scrum tasks from the 'rm_scrum_task' table.
    def list_scrum_tasks(
        auth_manager: AuthManager,
        server_config: ServerConfig,
        params: Dict[str, Any],
    ) -> Dict[str, Any]:
        """
        List scrum tasks from ServiceNow.
    
        Args:
            auth_manager: The authentication manager.
            server_config: The server configuration.
            params: The parameters for listing scrum tasks.
    
        Returns:
            A list of scrum tasks.
        """
        # Unwrap and validate parameters
        result = _unwrap_and_validate_params(
            params, 
            ListScrumTasksParams
        )
        
        if not result["success"]:
            return result
        
        validated_params = result["params"]
        
        # Build the query
        query_parts = []
        
        if validated_params.state:
            query_parts.append(f"state={validated_params.state}")
        if validated_params.assignment_group:
            query_parts.append(f"assignment_group={validated_params.assignment_group}")
        
        # Handle timeframe filtering
        if validated_params.timeframe:
            now = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
            if validated_params.timeframe == "upcoming":
                query_parts.append(f"start_date>{now}")
            elif validated_params.timeframe == "in-progress":
                query_parts.append(f"start_date<{now}^end_date>{now}")
            elif validated_params.timeframe == "completed":
                query_parts.append(f"end_date<{now}")
        
        # Add any additional query string
        if validated_params.query:
            query_parts.append(validated_params.query)
        
        # Combine query parts
        query = "^".join(query_parts) if query_parts else ""
        
        # 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",
            }
        
        # Make the API request
        url = f"{instance_url}/api/now/table/rm_scrum_task"
        
        params = {
            "sysparm_limit": validated_params.limit,
            "sysparm_offset": validated_params.offset,
            "sysparm_query": query,
            "sysparm_display_value": "true",
        }
        
        try:
            response = requests.get(url, headers=headers, params=params)
            response.raise_for_status()
            
            result = response.json()
            
            # Handle the case where result["result"] is a list
            scrum_tasks = result.get("result", [])
            count = len(scrum_tasks)
            
            return {
                "success": True,
                "scrum_tasks": scrum_tasks,
                "count": count,
                "total": count,  # Use count as total if total is not provided
            }
        except requests.exceptions.RequestException as e:
            logger.error(f"Error listing stories: {e}")
            return {
                "success": False,
                "message": f"Error listing stories: {str(e)}",
            }
  • Pydantic BaseModel defining the input schema/parameters for the list_scrum_tasks tool, including pagination (limit, offset), filters (state, assignment_group, timeframe, query).
    class ListScrumTasksParams(BaseModel):
        """Parameters for listing scrum tasks."""
    
        limit: Optional[int] = Field(10, description="Maximum number of records to return")
        offset: Optional[int] = Field(0, description="Offset to start from")
        state: Optional[str] = Field(None, description="Filter by state")
        assignment_group: Optional[str] = Field(None, description="Filter by assignment group")
        timeframe: Optional[str] = Field(None, description="Filter by timeframe (upcoming, in-progress, completed)")
        query: Optional[str] = Field(None, description="Additional query string")
  • Registration of the 'list_scrum_tasks' tool in the central tool_definitions dictionary returned by get_tool_definitions(). Maps the tool name to its handler function (list_scrum_tasks_tool), input schema (ListScrumTasksParams), return type hint, description, and serialization method.
    "list_scrum_tasks": (
        list_scrum_tasks_tool,
        ListScrumTasksParams,
        str,  # Expects JSON string
        "List scrum tasks from ServiceNow",
        "json",  # Tool returns list/dict
    ),
  • Import of the list_scrum_tasks handler from scrum_task_tools.py into the tools package __init__.py, making it available for use.
    from servicenow_mcp.tools.scrum_task_tools import (
        create_scrum_task,
        update_scrum_task,
        list_scrum_tasks,
    )
  • Inclusion of 'list_scrum_tasks' in the __all__ list of tools/__init__.py, explicitly exporting it from the package.
    "list_scrum_tasks",
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. 'List' implies a read operation, but the description doesn't mention pagination behavior, rate limits, authentication requirements, or what the return format looks like. For a tool with 6 parameters and no output schema, this leaves significant behavioral gaps.

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 appropriately sized for a list operation and front-loads the essential information. Every word earns its place in conveying the core functionality.

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 tool's complexity (6 parameters, no output schema, no annotations), the description is insufficient. It doesn't explain return values, pagination, filtering logic, or how parameters interact. For a list tool with multiple filtering options and no structured output documentation, the description should provide more context about what the tool returns and how to use it effectively.

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 already documents all 6 parameters thoroughly. The description adds no parameter-specific information beyond what's in the schema. According to guidelines, when schema coverage is high (>80%), the baseline score is 3 even with no param info in the description.

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 'List scrum tasks from ServiceNow' clearly states the verb ('List') and resource ('scrum tasks'), and specifies the source ('ServiceNow'). It distinguishes from siblings like 'list_stories' or 'list_epics' by focusing on scrum tasks, but doesn't explicitly differentiate from other list tools beyond the resource name.

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. It doesn't mention prerequisites, appropriate contexts, or compare with similar tools like 'list_stories' or 'list_epics' that might overlap in functionality. The agent must infer usage from the name alone.

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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