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Glama

List Invoices

list_invoices
Read-onlyIdempotent

List invoices and bills from a Xero accounting organisation. Returns compact invoice summaries (number, type, status, contact, dates, total, amount due, currency) for bookkeeping, accounts-receivable, and accounts-payable review. Supports Xero filter expressions and pagination.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pageNoPage number for pagination (default 1). Xero returns up to 100 invoices per page.
whereNoOptional Xero filter expression (e.g. 'Status=="AUTHORISED"' or 'Type=="ACCREC"'). Applied as the Xero `where` query parameter.
tenant_idNoOptional Xero tenant (organisation) id to target. If omitted, the first connected organisation is used. Get ids from list_organisations.

Schema Changelog

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

  1. Changed1 schema field changed
    • addedInput schema / examples
      Added value: +[
      +  {
      +    "page": 1,
      +    "tenant_id": "12345678-1234-1234-1234-123456789012",
      +    "where": "Status==\"AUTHORISED\""
      +  },
      +  {
      +    "where": "Type==\"ACCREC\""
      +  }
      +]
  2. First observed

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint, so the description doesn't need to repeat them. It adds value by specifying that it returns compact summaries and supports filtering and pagination.

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 two sentences, front-loaded with the action, and provides all necessary information without unnecessary words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no output schema, the description adequately explains return value (compact summaries with fields listed), optional tenant_id, and how to get tenant IDs, making it complete for a listing tool.

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

Parameters4/5

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

Schema coverage is 100%, and the description adds context by mentioning 'Xero filter expressions' and 'pagination', which reinforces the 'where' and 'page' parameters beyond the schema descriptions.

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 the tool lists invoices and bills from Xero, specifies returned fields (number, type, status, etc.), and mentions specific use cases (bookkeeping, AR/AP review), distinguishing it from sibling tools.

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

Usage Guidelines4/5

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

The description provides clear context on when to use (for reviewing invoices/bills) and mentions support for Xero filter expressions and pagination, but does not explicitly state alternatives or when not to use.

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

A3.8/5.0
Disambiguation4/5

Most tools have distinct purposes, but there is some overlap (e.g., ai_visibility_check and scan_competitor_ai_presence are related; memory tools remember/recall/forget form a clear subgroup). Descriptions are detailed enough to differentiate, but the broad scope may cause occasional mis-selection.

Naming Consistency2/5

Naming is inconsistent: some tools use verb_noun (list_accounts, get_profit_and_loss), others are single words (forget, recall), and some use snake_case with mixed verbs (ai_visibility_check, ask_pipeworx, bet_research). No uniform pattern makes the set harder to navigate.

Tool Count3/5

25 tools is high but not extreme given the broad scope (accounting, betting, data queries, npm, memory, etc.). However, the server tries to cover too many domains, making it feel bloated. Each tool is individually useful, but the count is borderline excessive for coherence.

Completeness2/5

The Xero accounting subset is incomplete: only list and get operations, no create/update/delete for invoices, contacts, or accounts. Other domains (betting, npm) are covered well, but the core accounting purpose has significant gaps that will hinder agents.