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mpeirone

zabbix-mcp-server

user_get

Retrieve users from Zabbix with optional filtering by user IDs, search criteria, or custom filters. Returns a JSON-formatted list of users for streamlined integration and analysis.

Instructions

Get users from Zabbix with optional filtering.

Args:
    userids: List of user IDs to retrieve
    output: Output format
    search: Search criteria
    filter: Filter criteria
    
Returns:
    str: JSON formatted list of users

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
filterNo
outputNoextend
searchNo
useridsNo

Implementation Reference

  • The main handler function for the 'user_get' tool. It is decorated with @mcp.tool(), which registers it as an MCP tool. The function retrieves users from the Zabbix API using the pyzabbix client, applies optional filters, and returns a formatted JSON response.
    def user_get(userids: Optional[List[str]] = None,
                 output: Union[str, List[str]] = "extend",
                 search: Optional[Dict[str, str]] = None,
                 filter: Optional[Dict[str, Any]] = None) -> str:
        """Get users from Zabbix with optional filtering.
        
        Args:
            userids: List of user IDs to retrieve
            output: Output format (extend or list of specific fields)
            search: Search criteria
            filter: Filter criteria
            
        Returns:
            str: JSON formatted list of users
        """
        client = get_zabbix_client()
        params = {"output": output}
        
        if userids:
            params["userids"] = userids
        if search:
            params["search"] = search
        if filter:
            params["filter"] = filter
        
        result = client.user.get(**params)
        return format_response(result)
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. The description mentions 'optional filtering' and describes the return format ('JSON formatted list of users'), but doesn't cover important behavioral aspects like authentication requirements, rate limits, error handling, pagination, or what happens when no users match the criteria. For a read operation with 4 parameters and no annotation coverage, this is insufficient.

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 reasonably concise with a clear two-part structure: purpose statement followed by parameter and return sections. However, the parameter section is overly terse - just listing names without explanation. The structure is front-loaded with the core purpose, but could be more efficient by integrating parameter semantics into the flow rather than as a bare list.

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 4 parameters with 0% schema coverage, no annotations, no output schema, and multiple sibling tools, the description is incomplete. It covers the basic purpose and return format but misses critical context: parameter semantics, usage guidelines, behavioral constraints, and differentiation from similar tools. For a tool with this complexity and lack of structured documentation, the description should provide much more guidance.

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

Parameters2/5

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

Schema description coverage is 0%, so the schema provides no parameter documentation. The description lists parameter names (userids, output, search, filter) but gives minimal semantic context. It doesn't explain what 'output format' means, what 'search criteria' entails, how 'filter criteria' differs from search, or provide examples of valid values. The description adds some value by naming parameters but doesn't adequately compensate for the complete lack of schema documentation.

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 tool's purpose: 'Get users from Zabbix with optional filtering.' It specifies the verb ('Get'), resource ('users'), and system ('Zabbix'), and mentions optional filtering. However, it doesn't explicitly differentiate from sibling tools like user_create, user_delete, or user_update, which would require more specific scope definition.

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. While it mentions 'optional filtering,' it doesn't specify when filtering is appropriate, what the default behavior is, or how this tool differs from other user-related tools like user_create or user_update. There's no mention of prerequisites, error conditions, or typical use cases.

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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