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vparlapalli490

ServiceNow MCP Server

list_workflows

Retrieve and filter workflow records from ServiceNow to manage automation processes, with options to limit results and apply status or name filters.

Instructions

List workflows from ServiceNow

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum number of records to return
offsetNoOffset to start from
activeNoFilter by active status
nameNoFilter by name (contains)
queryNoAdditional query string

Implementation Reference

  • The handler function that executes the list_workflows tool logic, querying the ServiceNow wf_workflow table API with parameters and returning formatted results.
    def list_workflows(
        auth_manager: AuthManager,
        server_config: ServerConfig,
        params: Dict[str, Any],
    ) -> Dict[str, Any]:
        """
        List workflows from ServiceNow.
        
        Args:
            auth_manager: Authentication manager
            server_config: Server configuration
            params: Parameters for listing workflows
            
        Returns:
            Dictionary containing the list of workflows
        """
        params = _unwrap_params(params, ListWorkflowsParams)
        
        # 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)}
        
        # Convert parameters to ServiceNow query format
        query_params = {
            "sysparm_limit": params.get("limit", 10),
            "sysparm_offset": params.get("offset", 0),
        }
        
        # Build query string
        query_parts = []
        
        if params.get("active") is not None:
            query_parts.append(f"active={str(params['active']).lower()}")
        
        if params.get("name"):
            query_parts.append(f"nameLIKE{params['name']}")
        
        if params.get("query"):
            query_parts.append(params["query"])
        
        if query_parts:
            query_params["sysparm_query"] = "^".join(query_parts)
        
        # Make the API request
        try:
            headers = auth_manager.get_headers()
            url = f"{server_config.instance_url}/api/now/table/wf_workflow"
            
            response = requests.get(url, headers=headers, params=query_params)
            response.raise_for_status()
            
            result = response.json()
            return {
                "workflows": result.get("result", []),
                "count": len(result.get("result", [])),
                "total": int(response.headers.get("X-Total-Count", 0)),
            }
        except requests.RequestException as e:
            logger.error(f"Error listing workflows: {e}")
            return {"error": str(e)}
        except Exception as e:
            logger.error(f"Unexpected error listing workflows: {e}")
            return {"error": str(e)}
  • Pydantic model defining the input schema (parameters) for the list_workflows tool.
    class ListWorkflowsParams(BaseModel):
        """Parameters for listing workflows."""
        
        limit: Optional[int] = Field(10, description="Maximum number of records to return")
        offset: Optional[int] = Field(0, description="Offset to start from")
        active: Optional[bool] = Field(None, description="Filter by active status")
        name: Optional[str] = Field(None, description="Filter by name (contains)")
        query: Optional[str] = Field(None, description="Additional query string")
  • Tool definition and registration entry for 'list_workflows' used by the MCP server to register the tool with its handler, schema, description, and serialization details.
    "list_workflows": (
        list_workflows_tool,
        ListWorkflowsParams,
        str,  # Expects JSON string
        "List workflows from ServiceNow",
        "json",  # Tool returns list/dict
    ),
  • Helper function to unwrap and validate input parameters using the Pydantic schema.
    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 resolve and validate 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 the full burden of behavioral disclosure. 'List workflows' implies a read-only operation, but the description doesn't specify whether this requires authentication, what permissions are needed, whether results are paginated (beyond what the schema indicates), what format the output takes, or any rate limits. For a tool with 5 parameters and no 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 extremely concise at just 4 words ('List workflows from ServiceNow'). It's front-loaded with the core action and resource, with zero wasted words. Every element earns its place by establishing the basic purpose 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 tool with 5 parameters, no annotations, and no output schema, the description is insufficiently complete. While concise, it doesn't address key contextual questions: what information is returned about each workflow, how results are ordered, whether this lists all workflows or just certain types, or how it relates to other workflow tools. The absence of output schema means the description should ideally provide some indication of return format.

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?

The schema description coverage is 100%, with each parameter clearly documented in the input schema. The description adds no additional parameter information beyond what's already in the structured schema. According to the scoring rules, when schema_description_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 verb ('List') and resource ('workflows from ServiceNow'), making the purpose immediately understandable. It distinguishes this as a read operation rather than a create/update/delete workflow tool. However, it doesn't explicitly differentiate from sibling tools like 'list_workflow_versions' or 'get_workflow_details' which also retrieve workflow information.

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. With sibling tools like 'list_workflow_versions', 'get_workflow_details', and 'get_workflow_activities' available, there's no indication whether this tool provides a comprehensive list, summary information, or how it differs from other listing/retrieval tools in the workflow domain.

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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