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ServiceNow MCP Server

deactivate_workflow

Disable a specific workflow in ServiceNow by providing its ID, ensuring it no longer executes automated processes within the platform.

Instructions

Deactivate a workflow in ServiceNow

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
paramsYes

Implementation Reference

  • The core handler function that performs the deactivation by sending a PATCH request to the ServiceNow wf_workflow table API endpoint to set active=false.
    def deactivate_workflow(
        auth_manager: AuthManager,
        server_config: ServerConfig,
        params: Dict[str, Any],
    ) -> Dict[str, Any]:
        """
        Deactivate a workflow in ServiceNow.
        
        Args:
            auth_manager: Authentication manager
            server_config: Server configuration
            params: Parameters for deactivating a workflow
            
        Returns:
            Dict[str, Any]: Deactivated workflow details
        """
        # Unwrap parameters if needed
        params = _unwrap_params(params, DeactivateWorkflowParams)
        
        # 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"}
        
        # Prepare data for the API request
        data = {
            "active": "false",
        }
        
        # 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.patch(url, headers=headers, json=data)
            response.raise_for_status()
            
            result = response.json()
            return {
                "workflow": result.get("result", {}),
                "message": "Workflow deactivated successfully",
            }
        except requests.RequestException as e:
            logger.error(f"Error deactivating workflow: {e}")
            return {"error": str(e)}
        except Exception as e:
            logger.error(f"Unexpected error deactivating workflow: {e}")
            return {"error": str(e)}
  • Pydantic BaseModel defining the input schema for the tool, requiring a workflow_id.
    class DeactivateWorkflowParams(BaseModel):
        """Parameters for deactivating a workflow."""
        
        workflow_id: str = Field(..., description="Workflow ID or sys_id")
  • Registration of the tool in the central get_tool_definitions() dictionary, associating the name with the imported handler function, schema, return type, description, and serialization method.
    "deactivate_workflow": (
        deactivate_workflow_tool,
        DeactivateWorkflowParams,
        str,
        "Deactivate a workflow in ServiceNow",
        "str",  # Tool returns simple message
    ),
  • Import of the deactivate_workflow handler into the tools package namespace for exposure.
    deactivate_workflow,
  • Helper function used by the handler to normalize auth_manager and server_config arguments, handling potential order swaps.
    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?

With no annotations provided, the description carries full burden for behavioral disclosure. It states the action ('deactivate') which implies mutation, but doesn't disclose whether this requires specific permissions, whether the deactivation is reversible, what happens to active instances, or any rate limits. 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 waste. It's appropriately sized for a simple tool and front-loads the essential information without unnecessary elaboration.

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 no annotations, no output schema, and 0% schema description coverage, the description is inadequate. It doesn't explain what 'deactivate' means operationally, what the response looks like, or any behavioral implications. Given the complexity of workflow management and the lack of structured documentation, more context is needed.

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 0%, so the description must compensate. However, the description provides no information about the single parameter 'workflow_id' beyond what's in the schema. The schema already documents this parameter adequately, so the baseline of 3 is appropriate despite the coverage gap.

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 ('deactivate') and target resource ('a workflow in ServiceNow'), providing specific verb+resource information. However, it doesn't distinguish this tool from its sibling 'activate_workflow' beyond the opposite action, missing explicit differentiation about when to use one versus the other.

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 is provided about when to use this tool versus alternatives like 'activate_workflow' or 'update_workflow'. The description states what it does but offers no context about appropriate use cases, prerequisites, or exclusions.

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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