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ServiceNow MCP Server

get_workflow_details

Retrieve detailed information about a specific workflow, including versions, from ServiceNow using its ID. This tool extracts workflow data via the ServiceNow MCP Server for streamlined access.

Instructions

Get detailed information about a specific workflow

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
paramsYes

Implementation Reference

  • Handler function that retrieves detailed information about a specific workflow by making a GET request to the ServiceNow wf_workflow table API endpoint.
    def get_workflow_details(
        auth_manager: AuthManager,
        server_config: ServerConfig,
        params: Dict[str, Any],
    ) -> Dict[str, Any]:
        """
        Get detailed information about a specific workflow.
        
        Args:
            auth_manager: Authentication manager
            server_config: Server configuration
            params: Parameters for getting workflow details
            
        Returns:
            Dictionary containing the workflow details
        """
        params = _unwrap_params(params, GetWorkflowDetailsParams)
        
        # Get the correct auth_manager and server_config
        try:
            auth_manager, server_config = _get_auth_and_config(auth_manager, server_config)
        except ValueError as e:
            logger.error(f"Error getting auth and config: {e}")
            return {"error": str(e)}
        
        workflow_id = params.get("workflow_id")
        if not workflow_id:
            return {"error": "Workflow ID is required"}
        
        # Make the API request
        try:
            headers = auth_manager.get_headers()
            url = f"{server_config.instance_url}/api/now/table/wf_workflow/{workflow_id}"
            
            response = requests.get(url, headers=headers)
            response.raise_for_status()
            
            result = response.json()
            return {
                "workflow": result.get("result", {}),
            }
        except requests.RequestException as e:
            logger.error(f"Error getting workflow details: {e}")
            return {"error": str(e)}
        except Exception as e:
            logger.error(f"Unexpected error getting workflow details: {e}")
            return {"error": str(e)}
  • Pydantic model defining the input parameters for the get_workflow_details tool: workflow_id (required) and include_versions (optional).
    class GetWorkflowDetailsParams(BaseModel):
        """Parameters for getting workflow details."""
        
        workflow_id: str = Field(..., description="Workflow ID or sys_id")
        include_versions: Optional[bool] = Field(False, description="Include workflow versions")
  • Registration of the get_workflow_details tool in the central tool definitions dictionary, specifying the implementation function, input schema model, return type hint, description, and serialization method.
    "get_workflow_details": (
        get_workflow_details_tool,
        GetWorkflowDetailsParams,
        str,  # Expects JSON string
        "Get detailed information about a specific workflow",
        "json",  # Tool returns list/dict
    ),
  • Helper function to unwrap parameters from Pydantic model to dict if necessary, used at the start of the handler.
    def _unwrap_params(params: Any, param_class: Type[T]) -> Dict[str, Any]:
        """
        Unwrap parameters if they're wrapped in a Pydantic model.
        This helps handle cases where the parameters are passed as a model instead of a dict.
        """
        if isinstance(params, dict):
            return params
        if isinstance(params, param_class):
            return params.dict(exclude_none=True)
        return params
  • Helper function to correctly order and identify auth_manager and server_config arguments, handling possible swapped order, used in the handler.
    def _get_auth_and_config(
        auth_manager_or_config: Union[AuthManager, ServerConfig],
        server_config_or_auth: Union[ServerConfig, AuthManager],
    ) -> tuple[AuthManager, ServerConfig]:
        """
        Get the correct auth_manager and server_config objects.
        
        This function handles the case where the parameters might be swapped.
        
        Args:
            auth_manager_or_config: Either an AuthManager or a ServerConfig.
            server_config_or_auth: Either a ServerConfig or an AuthManager.
            
        Returns:
            tuple[AuthManager, ServerConfig]: The correct auth_manager and server_config.
            
        Raises:
            ValueError: If the parameters are not of the expected types.
        """
        # Check if the parameters are in the correct order
        if isinstance(auth_manager_or_config, AuthManager) and isinstance(server_config_or_auth, ServerConfig):
            return auth_manager_or_config, server_config_or_auth
        
        # Check if the parameters are swapped
        if isinstance(auth_manager_or_config, ServerConfig) and isinstance(server_config_or_auth, AuthManager):
            return server_config_or_auth, auth_manager_or_config
        
        # If we get here, at least one of the parameters is not of the expected type
        if hasattr(auth_manager_or_config, "get_headers"):
            auth_manager = auth_manager_or_config
        elif hasattr(server_config_or_auth, "get_headers"):
            auth_manager = server_config_or_auth
        else:
            raise ValueError("Cannot find get_headers method in either auth_manager or server_config")
        
        if hasattr(auth_manager_or_config, "instance_url"):
            server_config = auth_manager_or_config
        elif hasattr(server_config_or_auth, "instance_url"):
            server_config = server_config_or_auth
        else:
            raise ValueError("Cannot find instance_url attribute in either auth_manager or server_config")
        
        return auth_manager, server_config
Behavior2/5

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. It states the tool is for getting information, implying a read-only operation, but doesn't specify permissions, rate limits, error conditions, or what 'detailed information' includes. For a tool with zero annotation coverage, this is insufficient to inform the agent about behavioral traits.

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

Conciseness4/5

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

The description is a single, clear sentence that efficiently states the tool's purpose without unnecessary words. It's front-loaded with the core action and resource, making it easy to parse. However, it could be more specific to improve utility without sacrificing conciseness.

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 lack of annotations and output schema, the description is incomplete. It doesn't explain what 'detailed information' includes, how to handle the 'include_versions' parameter, or the response format. For a tool in a complex environment with many siblings, more context is needed to guide effective use.

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

Parameters4/5

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

The description doesn't explicitly mention parameters, but with only one required parameter ('workflow_id'), the tool's purpose inherently implies its use. Schema description coverage is 0%, but the parameter is straightforward (a workflow ID). The description's focus on 'specific workflow' aligns with the parameter, adding minimal but adequate context beyond the schema.

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 states the tool's purpose as 'Get detailed information about a specific workflow', which is clear but vague. It specifies the verb ('Get') and resource ('workflow'), but doesn't distinguish it from sibling tools like 'get_workflow_activities' or 'list_workflows'. The description is adequate but lacks specificity about what 'detailed information' entails.

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 sibling tools like 'list_workflows' for listing workflows or 'get_workflow_activities' for activity details, nor does it specify prerequisites or contexts for usage. This leaves the agent without direction on tool selection.

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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