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ServiceNow MCP Server

update_changeset

Modify an existing ServiceNow changeset by updating its name, description, developer, or state. Ensures accurate and current changeset details for streamlined development workflows.

Instructions

Update an existing changeset in ServiceNow

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
paramsYes

Implementation Reference

  • The main handler function that implements the update_changeset tool logic, including parameter validation, API call to patch the changeset, and error handling.
    def update_changeset(
        auth_manager: AuthManager,
        server_config: ServerConfig,
        params: Union[Dict[str, Any], UpdateChangesetParams],
    ) -> Dict[str, Any]:
        """
        Update an existing changeset in ServiceNow.
    
        Args:
            auth_manager: The authentication manager.
            server_config: The server configuration.
            params: The parameters for updating a changeset. Can be a dictionary or a UpdateChangesetParams object.
    
        Returns:
            The updated changeset.
        """
        # Unwrap and validate parameters
        result = _unwrap_and_validate_params(
            params, 
            UpdateChangesetParams, 
            required_fields=["changeset_id"]
        )
        
        if not result["success"]:
            return result
        
        validated_params = result["params"]
        
        # Prepare the request data
        data = {}
        
        # Add optional fields if provided
        if validated_params.name:
            data["name"] = validated_params.name
        if validated_params.description:
            data["description"] = validated_params.description
        if validated_params.state:
            data["state"] = validated_params.state
        if validated_params.developer:
            data["developer"] = validated_params.developer
        
        # If no fields to update, return error
        if not data:
            return {
                "success": False,
                "message": "No fields to update",
            }
        
        # Get the instance URL
        instance_url = _get_instance_url(auth_manager, server_config)
        if not instance_url:
            return {
                "success": False,
                "message": "Cannot find instance_url in either server_config or auth_manager",
            }
        
        # Get the headers
        headers = _get_headers(auth_manager, server_config)
        if not headers:
            return {
                "success": False,
                "message": "Cannot find get_headers method in either auth_manager or server_config",
            }
        
        # Add Content-Type header
        headers["Content-Type"] = "application/json"
        
        # Make the API request
        url = f"{instance_url}/api/now/table/sys_update_set/{validated_params.changeset_id}"
        
        try:
            response = requests.patch(url, json=data, headers=headers)
            response.raise_for_status()
            
            result = response.json()
            
            return {
                "success": True,
                "message": "Changeset updated successfully",
                "changeset": result["result"],
            }
        except requests.exceptions.RequestException as e:
            logger.error(f"Error updating changeset: {e}")
            return {
                "success": False,
                "message": f"Error updating changeset: {str(e)}",
            }
  • Pydantic model defining the input parameters for the update_changeset tool.
    class UpdateChangesetParams(BaseModel):
        """Parameters for updating a changeset."""
    
        changeset_id: str = Field(..., description="Changeset ID or sys_id")
        name: Optional[str] = Field(None, description="Name of the changeset")
        description: Optional[str] = Field(None, description="Description of the changeset")
        state: Optional[str] = Field(None, description="State of the changeset")
        developer: Optional[str] = Field(None, description="Developer responsible for the changeset")
  • Registration of the update_changeset tool in the get_tool_definitions dictionary, specifying the handler alias, schema, return type hint, description, and serialization method.
    "update_changeset": (
        update_changeset_tool,
        UpdateChangesetParams,
        str,  # Expects JSON string
        "Update an existing changeset in ServiceNow",
        "json_dict",  # Tool returns Pydantic model
    ),
  • Import of update_changeset function from changeset_tools, exposing it in the tools namespace.
    from servicenow_mcp.tools.changeset_tools import (
        add_file_to_changeset,
        commit_changeset,
        create_changeset,
        get_changeset_details,
        list_changesets,
        publish_changeset,
        update_changeset,
    )
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 for behavioral disclosure. While 'Update' implies a mutation operation, the description doesn't specify required permissions, whether changes are reversible, potential side effects, or what happens to unspecified fields. It lacks critical context for a mutation tool with zero annotation coverage.

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 basic tool description and front-loads the essential information (action and resource).

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 5 parameters, 0% schema description coverage, no annotations, and no output schema, the description is severely incomplete. It covers only the basic purpose without addressing parameter meanings, behavioral traits, usage context, or expected outcomes, leaving significant gaps for agent understanding.

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

Parameters1/5

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

The description mentions no parameters at all, while the input schema shows 5 parameters (changeset_id, description, developer, name, state) with 0% schema description coverage. The description fails to compensate for this complete lack of parameter documentation in the schema, leaving all parameters semantically undefined.

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 changeset in ServiceNow'), providing a specific verb+resource combination. However, it doesn't differentiate this tool from sibling tools like 'update_change_request' or 'update_article', which follow the same pattern for different resources.

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 prerequisites (e.g., needing an existing changeset ID), when not to use it, or how it differs from related tools like 'create_changeset' or 'publish_changeset' in the sibling list.

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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