Skip to main content
Glama
javerthl

ServiceNow MCP Server

by javerthl

get_user

Retrieve specific user details from ServiceNow using user ID, username, or email address to access user information and manage user records.

Instructions

Get a specific user in ServiceNow

Input Schema

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

Implementation Reference

  • Main handler function for the 'get_user' tool. Queries the ServiceNow sys_user table API using provided user_id, username, or email, returns user details or error.
    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 schema/model for input parameters to the get_user tool, supporting search by user_id, user_name, or email.
    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")
  • Registration of the 'get_user' tool in the central tool_definitions dictionary used by the MCP server to dynamically register tools, linking the handler, schema, description, and serialization method.
    "get_user": (
        get_user_tool,
        GetUserParams,
        Dict[str, Any],  # Expects dict
        "Get a specific user in ServiceNow",
        "raw_dict",
    ),
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states 'Get a specific user' but doesn't mention authentication requirements, error handling (e.g., if no user is found), rate limits, or response format. This leaves significant gaps in understanding how the tool behaves beyond basic functionality.

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 no wasted words. It's front-loaded with the core action and resource, making it easy to parse quickly. Every part of the sentence contributes directly to understanding the tool's purpose.

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 3 parameters, no annotations, and no output schema, the description is insufficient. It doesn't explain how parameters interact (e.g., if multiple are provided), what the return value includes, or error conditions. Given the complexity and lack of structured data, more context is needed for effective use.

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 (email, user_id, user_name). The description adds no additional meaning beyond the schema, such as parameter precedence or usage examples. Given the high schema coverage, the baseline score of 3 is appropriate.

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 ('Get') and resource ('a specific user in ServiceNow'), making the purpose unambiguous. However, it doesn't differentiate from sibling tools like 'list_users' or 'get_article', which follow similar patterns, so it doesn't fully distinguish itself from alternatives.

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' for multiple users or other 'get_' tools for different resources. It lacks explicit context, prerequisites, or exclusions, leaving usage decisions unclear.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/javerthl/servicenow-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server