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vparlapalli490

ServiceNow MCP Server

list_change_requests

Retrieve and filter change requests from ServiceNow to monitor, track, and manage IT infrastructure modifications.

Instructions

List change requests from ServiceNow

Input Schema

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

Implementation Reference

  • The main handler function that implements the list_change_requests tool logic. It validates parameters using ListChangeRequestsParams, builds a ServiceNow Table API query based on filters, fetches change requests via GET /api/now/table/change_request, and returns the list with success status.
    def list_change_requests(
        auth_manager: AuthManager,
        server_config: ServerConfig,
        params: Dict[str, Any],
    ) -> Dict[str, Any]:
        """
        List change requests from ServiceNow.
    
        Args:
            auth_manager: The authentication manager.
            server_config: The server configuration.
            params: The parameters for listing change requests.
    
        Returns:
            A list of change requests.
        """
        # Unwrap and validate parameters
        result = _unwrap_and_validate_params(
            params, 
            ListChangeRequestsParams
        )
        
        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.type:
            query_parts.append(f"type={validated_params.type}")
        if validated_params.category:
            query_parts.append(f"category={validated_params.category}")
        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/change_request"
        
        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
            change_requests = result.get("result", [])
            count = len(change_requests)
            
            return {
                "success": True,
                "change_requests": change_requests,
                "count": count,
                "total": count,  # Use count as total if total is not provided
            }
        except requests.exceptions.RequestException as e:
            logger.error(f"Error listing change requests: {e}")
            return {
                "success": False,
                "message": f"Error listing change requests: {str(e)}",
            }
  • Pydantic model defining the input parameters for the list_change_requests tool, including pagination (limit, offset), filters (state, type, category, etc.), and custom query.
    class ListChangeRequestsParams(BaseModel):
        """Parameters for listing change requests."""
    
        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")
        type: Optional[str] = Field(None, description="Filter by type (normal, standard, emergency)")
        category: Optional[str] = Field(None, description="Filter by category")
        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")
  • MCP tool registration in get_tool_definitions(). Maps 'list_change_requests' to the aliased handler (list_change_requests_tool), input schema (ListChangeRequestsParams), description, and serialization ('json').
    "list_change_requests": (
        list_change_requests_tool,
        ListChangeRequestsParams,
        str,  # Expects JSON string
        "List change requests from ServiceNow",
        "json",  # Tool returns list/dict
    ),
  • Import of list_change_requests function from change_tools.py into the tools module namespace.
    list_change_requests,
  • Import alias for the handler function used in MCP tool registration (list_change_requests_tool).
    list_change_requests as list_change_requests_tool,
Behavior2/5

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

With no annotations provided, the description carries full burden but only states the action ('list') without behavioral details. It doesn't disclose if this is read-only (implied but not explicit), how results are returned (e.g., pagination, format), rate limits, authentication needs, or error handling. For a tool with 8 parameters and no annotations, this is a significant gap in 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 a single, efficient sentence with zero waste—'List change requests from ServiceNow' is front-loaded and to the point. Every word earns its place by specifying action, resource, and source without redundancy or fluff.

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 tool with 8 parameters, no annotations, and no output schema, the description is incomplete. It lacks details on return values (e.g., structure, fields), behavioral traits (e.g., pagination, sorting), and differentiation from siblings. Given the complexity and missing structured data, the description should provide more context to guide effective use.

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%, with each parameter well-documented in the schema (e.g., 'limit' as 'Maximum number of records to return'). The description adds no parameter-specific information beyond what's in the schema, so it meets the baseline of 3 but doesn't compensate with additional context like examples or constraints.

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

Purpose3/5

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

The description 'List change requests from ServiceNow' clearly states the verb ('list') and resource ('change requests'), but it's vague about scope and doesn't distinguish from sibling tools like 'list_changesets' or 'get_change_request_details'. It specifies the source (ServiceNow) but lacks detail on what 'list' entails (e.g., filtered vs. all).

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?

No guidance on when to use this tool versus alternatives like 'get_change_request_details' for single records or 'list_changesets' for related entities. The description implies a listing function but doesn't specify use cases (e.g., monitoring, reporting) or prerequisites, leaving the agent to infer usage from context 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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