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vparlapalli490

ServiceNow MCP Server

get_user

Retrieve specific user details from ServiceNow by providing user ID, username, or email address to access user information.

Instructions

Get a specific user in ServiceNow

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
user_idNoUser ID or sys_id
user_nameNoUsername of the user
emailNoEmail address of the user

Implementation Reference

  • The handler function that executes the core logic of the 'get_user' tool by querying the ServiceNow sys_user table API with the provided parameters.
    def get_user(
        config: ServerConfig,
        auth_manager: AuthManager,
        params: GetUserParams,
    ) -> dict:
        """
        Get a user from ServiceNow.
    
        Args:
            config: Server configuration.
            auth_manager: Authentication manager.
            params: Parameters for getting the user.
    
        Returns:
            Dictionary containing user details.
        """
        api_url = f"{config.api_url}/table/sys_user"
        query_params = {}
    
        # Build query parameters
        if params.user_id:
            query_params["sysparm_query"] = f"sys_id={params.user_id}"
        elif params.user_name:
            query_params["sysparm_query"] = f"user_name={params.user_name}"
        elif params.email:
            query_params["sysparm_query"] = f"email={params.email}"
        else:
            return {"success": False, "message": "At least one search parameter is required"}
    
        query_params["sysparm_limit"] = "1"
        query_params["sysparm_display_value"] = "true"
    
        # Make request
        try:
            response = requests.get(
                api_url,
                params=query_params,
                headers=auth_manager.get_headers(),
                timeout=config.timeout,
            )
            response.raise_for_status()
    
            result = response.json().get("result", [])
            if not result:
                return {"success": False, "message": "User not found"}
    
            return {"success": True, "message": "User found", "user": result[0]}
    
        except requests.RequestException as e:
            logger.error(f"Failed to get user: {e}")
            return {"success": False, "message": f"Failed to get user: {str(e)}"}
  • Pydantic BaseModel defining the input schema/parameters for the get_user tool.
    class GetUserParams(BaseModel):
        """Parameters for getting a user."""
    
        user_id: Optional[str] = Field(None, description="User ID or sys_id")
        user_name: Optional[str] = Field(None, description="Username of the user")
        email: Optional[str] = Field(None, description="Email address of the user")
  • MCP tool registration entry in the central tool_definitions dictionary, mapping 'get_user' name to its handler function, input schema, return type hint, description, and serialization method.
    "get_user": (
        get_user_tool,
        GetUserParams,
        Dict[str, Any],  # Expects dict
        "Get a specific user in ServiceNow",
        "raw_dict",
    ),
  • Import and export of the get_user function in the tools package __init__.py, making it available for server registration.
    from servicenow_mcp.tools.user_tools import (
        create_user,
        update_user,
        get_user,
        list_users,
        create_group,
        update_group,
        add_group_members,
        remove_group_members,
        list_groups,
    )
  • Inclusion of 'get_user' in the __all__ export list for the tools module.
    "get_user",
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 'Get' implies a read operation, it doesn't specify whether this requires authentication, has rate limits, returns partial/full user data, or handles errors. For a read tool with zero annotation coverage, this leaves significant behavioral gaps.

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 that states the core purpose without unnecessary words. It's appropriately sized for a simple retrieval tool and front-loads the essential information.

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's moderate complexity (retrieving specific user data), absence of annotations, and lack of output schema, the description is insufficient. It doesn't explain what user data is returned, how multiple parameters interact, or error conditions. For a tool with no structured behavioral or output documentation, the description should provide more complete context.

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 input schema has 100% description coverage, with each parameter clearly documented. The description adds no additional parameter information beyond what's in the schema. According to 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 action ('Get') and resource ('a specific user in ServiceNow'), making the purpose immediately understandable. However, it doesn't differentiate this tool from sibling tools like 'list_users' or 'get_user' (if there were multiple user retrieval tools), which prevents a perfect score.

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 'list_users' (which appears in the sibling list). There's no mention of prerequisites, constraints, or comparison with other user-related tools, leaving the agent without contextual usage direction.

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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