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JLKmach

ServiceNow MCP Server

by JLKmach

list_workflows

Retrieve and filter workflows from ServiceNow to manage automation processes, with options to limit results, filter by status, and search by name.

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 implements the core logic of the 'list_workflows' tool. It queries the ServiceNow 'wf_workflow' table API with parameters, handles authentication, builds queries for filtering, and returns a structured response with workflows list, count, and total.
    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 BaseModel defining the input schema/parameters for the list_workflows tool, including optional fields for limit, offset, active filter, name filter, and custom query.
    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 registration entry in the central get_tool_definitions() function, mapping the tool name to its handler (list_workflows_tool), input schema (ListWorkflowsParams), return type hint, description, and serialization method.
    "list_workflows": (
        list_workflows_tool,
        ListWorkflowsParams,
        str,  # Expects JSON string
        "List workflows from ServiceNow",
        "json",  # Tool returns list/dict
    ),
  • Import statement in tools/__init__.py that exposes list_workflows for use in tool_utils.py and other modules.
    from servicenow_mcp.tools.workflow_tools import (
        activate_workflow,
        add_workflow_activity,
        create_workflow,
        deactivate_workflow,
        delete_workflow_activity,
        get_workflow_activities,
        get_workflow_details,
        list_workflow_versions,
        list_workflows,
        reorder_workflow_activities,
        update_workflow,
        update_workflow_activity,
    )
  • Helper function used by list_workflows (and other tools) to flexibly resolve 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?

No annotations are provided, so the description carries full burden. 'List workflows' implies a read-only operation, but the description doesn't disclose pagination behavior, rate limits, authentication requirements, or what fields are returned. For a tool with 5 parameters and no output schema, this is a significant behavioral information gap.

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 extremely concise - just 4 words. While this is efficient, it may be too brief given the tool's complexity (5 parameters, no output schema). Every word earns its place, but the description might benefit from slightly more context given the lack of annotations.

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 tool has 5 parameters, no annotations, and no output schema, the description is incomplete. It doesn't explain what 'workflows' means in this context, what data is returned, or how results are structured. For a list operation with filtering capabilities, more context about the return format and typical use cases would be helpful.

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 fully documents all 5 parameters. The description adds no parameter information beyond what's in the schema. According to scoring rules, when schema coverage is high (>80%), the baseline is 3 even with no param info in description.

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 workflows from ServiceNow' clearly states the verb ('List') and resource ('workflows'), but it's vague about scope and doesn't distinguish from sibling tools like 'list_workflow_versions' or 'get_workflow_details'. It provides basic purpose but lacks specificity about what kind of listing this performs.

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 many sibling tools available (like list_workflow_versions, get_workflow_details, get_workflow_activities), there's no indication of when this list operation is appropriate versus more specific retrieval tools.

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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