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LicenseSpring MCP Server

by stier1ba

Get Customer License Users

get_customer_license_users

Retrieve users associated with a specific license for a product and customer using the LicenseSpring MCP Server to manage license data effectively.

Instructions

Get customer license users for a specific license

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
customerYes
productYes

Implementation Reference

  • Handler function that queries the LicenseSpring License API endpoint /api/v4/customer_license_users with product and customer parameters, returns JSON response or error.
    }, async ({ product, customer }) => {
      try {
        const queryParams = new URLSearchParams({
          product,
          customer,
        });
        const response = await apiClient.get(`/api/v4/customer_license_users?${queryParams}`);
    
        return {
          content: [{
            type: 'text',
            text: JSON.stringify(response.data, null, 2),
          }],
        };
      } catch (error) {
        return {
          content: [{
            type: 'text',
            text: `Error getting customer license users: ${handleApiError(error)}`,
          }],
          isError: true,
        };
      }
    });
  • Zod validation schema for tool inputs: product (required string) and customer (required string).
    inputSchema: {
      product: z.string().min(1, 'Product code is required'),
      customer: z.string().min(1, 'Customer email or account code is required'),
    },
  • MCP server tool registration for 'get_customer_license_users' including title, description, input schema, and inline handler function.
    server.registerTool('get_customer_license_users', {
      title: 'Get Customer License Users',
      description: 'Get customer license users for a specific license',
      inputSchema: {
        product: z.string().min(1, 'Product code is required'),
        customer: z.string().min(1, 'Customer email or account code is required'),
      },
    }, async ({ product, customer }) => {
      try {
        const queryParams = new URLSearchParams({
          product,
          customer,
        });
        const response = await apiClient.get(`/api/v4/customer_license_users?${queryParams}`);
    
        return {
          content: [{
            type: 'text',
            text: JSON.stringify(response.data, null, 2),
          }],
        };
      } catch (error) {
        return {
          content: [{
            type: 'text',
            text: `Error getting customer license users: ${handleApiError(error)}`,
          }],
          isError: true,
        };
      }
    });
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states a read operation ('Get'), implying it's likely non-destructive, but doesn't cover critical aspects like authentication needs, rate limits, error handling, or response format. This is a significant gap for a 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 that directly states the tool's purpose without any fluff or redundancy. It's appropriately sized and front-loaded, making it easy to parse quickly.

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 2 parameters, no annotations, no output schema, and 0% schema coverage, the description is incomplete. It lacks details on parameter usage, behavioral traits, and expected outputs, making it inadequate for an agent to reliably invoke the tool without additional context or trial-and-error.

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 details. The description mentions 'for a specific license' but doesn't explain what 'customer' and 'product' parameters represent, their expected formats, or how they relate to the license. It adds minimal value beyond the schema, failing to compensate for the coverage gap.

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 ('customer license users') with the scope 'for a specific license', making the purpose understandable. However, it doesn't differentiate from sibling tools like 'get_product_details' or 'get_versions', which also retrieve information but for different resources, so it misses full sibling distinction.

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, context, or exclusions, such as whether it's for active licenses only or how it differs from other 'get' tools in the sibling list, leaving the agent with no 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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