Add VAT to a net amount or extract VAT from a gross amount at any rate (e.g. 21 for Dutch BTW). Returns exact net, VAT, and gross amounts rounded to cents.
| Name | Required | Description | Default |
|---|---|---|---|
| mode | Yes | add = amount is net, add VAT on top; extract = amount is gross, split out VAT | |
| rate | Yes | VAT rate in percent | |
| amount | Yes | The amount |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full behavioral burden. It usefully discloses that the tool returns exact net, VAT, and gross amounts rounded to cents, which goes beyond the schema and sets expectations about output precision. It does not mention edge-case handling, but this is a simple pure calculation and the disclosure is adequate.
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?
The description is two tightly written sentences with no filler. The core operation and modes are front-loaded, and the return-value behavior is stated in the second sentence. Every clause earns its place.
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 low-complexity calculation tool, the description is complete: it explains both modes, the rate semantics, and the exact return components. The schema covers all required parameters, so an agent has everything needed to invoke the tool correctly.
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?
Schema description coverage is 100%, so the schema already documents all three parameters fully. The description does add helpful context by clarifying that 'net' applies to add mode and 'gross' to extract mode, plus the Dutch BTW example for rate, but it does not meaningfully extend the parameter semantics beyond what the schema states.
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 clearly states the tool's two modes—add VAT to a net amount or extract it from a gross amount—using specific verbs and the resource (VAT). It also immediately distinguishes itself from the sibling tool check_vat_number_format, which validates VAT numbers rather than calculating amounts.
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 for when to use the tool: whenever VAT needs to be added or extracted at any rate. It does not explicitly name exclusions or alternatives, but the usage context is unambiguous and leaves little room for misapplication.
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 have clearly distinct purposes, but some pairs could be confused: html_to_pdf vs url_to_pdf both produce PDFs, read_page vs url_screenshot both fetch a URL, and generate_test_bsn vs generate_brp_test_data both generate Dutch test data. Detailed descriptions mitigate most ambiguity, so agents can usually select correctly.
All tool names follow a consistent snake_case convention with predictable verb_noun patterns (e.g., generate_*, validate_*, memory_*, url_*). The naming is uniform and makes each tool's function easily inferable from its name.
35 tools is a heavy surface for any MCP server, even a general-purpose toolbox. The large number of niche Dutch-specific tools (BRP, UPA, BSN, holidays) may overwhelm agents and increase selection complexity. The server could benefit from splitting into smaller, focused servers.
The server covers a wide range of utilities, but there are notable gaps: no hash generation, no json_to_csv counterpart, and the workflow sub-domain only offers list/run without create/delete. Core utilities are present, but some obvious counterparts and lifecycle operations are missing.