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Glama

lago

by io.usefulapi

Create customer

lago_create_customer
Destructive

Creates a customer in Lago (additive). Lago API: POST /customers with body { "customer": { ... } }.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlNoCustomer URL.
nameNoFull name of the customer.
emailNoEmail of the customer.
phoneNoPhone number.
countryNoBilling country code (ISO 3166 alpha-2).
currencyNoCustomer currency (ISO 4217).
metadataNoStructured metadata to attach to the customer (Lago expects an array of {key, value, display_in_invoice?} objects).
timezoneNoCustomer timezone, e.g. America/New_York.
legal_nameNoLegal company name.
external_idYesThe customer external unique identifier (required, provided by your application).
legal_numberNoLegal company number.
tax_identification_numberNoTax identification number.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

B3.1/5.0
Behavior1/5

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

The description states the tool is 'additive' (creating a new record), which contradicts the annotation 'destructiveHint: true' (implying destructive behavior). This contradiction severely undermines transparency, and the description does not clarify the discrepancy beyond the API detail.

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 one sentence plus the API endpoint, front-loading the action. It is concise and avoids unnecessary details, earning a high score for efficiency.

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?

The description lacks information about return values (no output schema), and the contradiction between 'additive' and destructiveHint leaves agents uncertain about the tool's effects. For a tool with 12 parameters, more context on expected outcomes is needed.

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?

Schema coverage is 100% with all parameters well-described. The tool description does not add additional semantic value beyond what the schema already provides, meeting the baseline expectation.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states 'Creates a customer in Lago (additive)' with the specific API endpoint, making the verb and resource unambiguous. It distinguishes from sibling tools like lago_get_customer (read) and lago_list_customers (list).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage when a new customer needs to be created, but it does not provide explicit when-to-use or when-not-to-use guidance, nor does it mention alternatives among siblings like lago_get_customer for checking existence.

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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TDQS

A3.6/5.0
Disambiguation5/5

Each tool targets a distinct entity and action (e.g., lago_get_customer vs. lago_create_customer, lago_list_invoices vs. lago_get_invoice), with no overlapping purposes. The separation between analytics, customer, invoice, subscription, and other resource types is clear.

Naming Consistency5/5

All tools follow a consistent verb_noun pattern with lower_snake_case and the 'lago_' prefix. Actions like 'get', 'list', 'create', and 'retrieve-related' (e.g., lago_get_customer_current_usage) are uniform, making the naming predictable.

Tool Count4/5

With 24 tools, the server covers a broad range of billing/analytics operations. While slightly high, each tool serves a distinct purpose for reading or creating core entities and analytics. The count is well-scoped for its domain.

Completeness2/5

The server overwhelmingly focuses on read operations (list/get) with only two write tools (create_customer, create_event). Missing CRUD for invoices, subscriptions, plans, add-ons, coupons, credit notes, and wallets limits agents to mostly read-only workflows, creating significant gaps for managing billing lifecycles.

Resources