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vparlapalli490

ServiceNow MCP Server

update_workflow

Modify existing ServiceNow workflows by updating their name, description, table association, activation status, or custom attributes to adapt business processes.

Instructions

Update an existing workflow in ServiceNow

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
workflow_idYesWorkflow ID or sys_id
nameNoName of the workflow
descriptionNoDescription of the workflow
tableNoTable the workflow applies to
activeNoWhether the workflow is active
attributesNoAdditional attributes for the workflow

Implementation Reference

  • The main handler function that executes the tool logic: unwraps params, prepares PATCH data, sends request to ServiceNow wf_workflow table endpoint.
    def update_workflow(
        auth_manager: AuthManager,
        server_config: ServerConfig,
        params: Dict[str, Any],
    ) -> Dict[str, Any]:
        """
        Update an existing workflow in ServiceNow.
        
        Args:
            auth_manager: Authentication manager
            server_config: Server configuration
            params: Parameters for updating a workflow
            
        Returns:
            Dict[str, Any]: Updated workflow details
        """
        # Unwrap parameters if needed
        params = _unwrap_params(params, UpdateWorkflowParams)
        
        # 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 = {}
        
        if params.get("name"):
            data["name"] = params["name"]
        
        if params.get("description") is not None:
            data["description"] = params["description"]
        
        if params.get("table"):
            data["table"] = params["table"]
        
        if params.get("active") is not None:
            data["active"] = str(params["active"]).lower()
        
        if params.get("attributes"):
            # Add any additional attributes
            data.update(params["attributes"])
        
        if not data:
            return {"error": "No update parameters provided"}
        
        # 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 updated successfully",
            }
        except requests.RequestException as e:
            logger.error(f"Error updating workflow: {e}")
            return {"error": str(e)}
        except Exception as e:
            logger.error(f"Unexpected error updating workflow: {e}")
            return {"error": str(e)}
  • Pydantic BaseModel defining the input schema/parameters for the update_workflow tool.
    class UpdateWorkflowParams(BaseModel):
        """Parameters for updating a workflow."""
        
        workflow_id: str = Field(..., description="Workflow ID or sys_id")
        name: Optional[str] = Field(None, description="Name of the workflow")
        description: Optional[str] = Field(None, description="Description of the workflow")
        table: Optional[str] = Field(None, description="Table the workflow applies to")
        active: Optional[bool] = Field(None, description="Whether the workflow is active")
        attributes: Optional[Dict[str, Any]] = Field(None, description="Additional attributes for the workflow")
  • Tool registration in get_tool_definitions() dict: maps 'update_workflow' to handler (aliased import), schema, return type hint, description, and serialization method.
    "update_workflow": (
        update_workflow_tool,
        UpdateWorkflowParams,
        str,  # Expects JSON string
        "Update an existing workflow in ServiceNow",
        "json_dict",  # Tool returns Pydantic model
    ),
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. While 'Update' implies mutation, the description doesn't specify what permissions are required, whether changes are reversible, what happens to unspecified fields, or what the response contains. For a mutation tool with zero annotation coverage, this is inadequate.

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 tool with comprehensive schema documentation and gets straight to the point 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 and no output schema, the description is insufficient. It doesn't explain what 'updating' entails operationally, what happens to unspecified fields, whether the update is partial or complete, or what the tool returns. The agent lacks critical context for proper 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 already documents all 6 parameters thoroughly. The description adds no additional parameter information beyond what's in the schema. According to guidelines, when schema coverage is high (>80%), the baseline 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 clearly states the action ('Update') and resource ('an existing workflow in ServiceNow'), providing specific verb+resource pairing. However, it doesn't differentiate this tool from sibling 'update_workflow_activity' or explain what distinguishes updating a workflow from updating workflow activities.

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_workflow' or 'update_workflow_activity'. There's no mention of prerequisites, appropriate contexts, or exclusions. 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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