List tax codes
list_tax_codesList the product tax codes Quaderno supports (id, name, description) — used as the tax_code on products / tax calculations. Quaderno API: GET /tax_codes.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
list_tax_codesList the product tax codes Quaderno supports (id, name, description) — used as the tax_code on products / tax calculations. Quaderno API: GET /tax_codes.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, and the description reinforces the read-only nature with 'Quaderno API: GET /tax_codes.' It also adds the returned field list, which is useful behavioral context given there is no output schema.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
One compact sentence plus an API endpoint reference: no filler or redundancy. The core purpose and usage context are front-loaded, and the technical detail is appended cleanly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-parameter, read-only list operation, the description provides the resource, returned fields, intended use, and API endpoint. It is complete enough for an agent to select and invoke the tool correctly without additional documentation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters and schema coverage is 100%, so there is no parameter ambiguity to resolve. The description adds purpose context, but parameters require no additional semantic explanation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('List') with a clear resource ('product tax codes Quaderno supports') and enumerates the returned fields (id, name, description). It also clarifies the resource's role as the tax_code for products/tax calculations, which distinguishes it from sibling tools like list_jurisdictions and calculate_tax.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives clear context: the codes are 'used as the tax_code on products / tax calculations,' so an agent knows when fetching them is relevant. It does not explicitly name alternatives or when-not conditions, but the practical context is strong enough to guide selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Most tools target distinct resources and actions, but create_invoice and create_transaction both generate tax-compliant sale documents, making their boundary unclear. calculate_tax also overlaps conceptually with the tax calculation embedded in create_transaction, though the descriptions help separate the read-only case.
The set follows a consistent verb_noun pattern across get_, list_, create_, and update_ tools, with clear singular/plural usage. calculate_tax and ping fit the style, but quaderno_request is a generic escape hatch that breaks the predictable naming convention.
At 23 tools, the server is on the heavy side and falls in the 16-25 range that feels less scoped than ideal. However, the count is somewhat justified by the many distinct entity types covered, including contacts, invoices, items, credit notes, expenses, receipts, jurisdictions, and webhooks.
Core workflows like calculating tax, creating invoices/transactions, and managing contacts/items are covered, and every exposed resource has get/list access. Missing update/delete operations for most resources, read-only webhooks, and no direct creation paths for expenses/receipts/credit notes leave notable lifecycle gaps.