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e-RUP KNF MCP Server

e-RUP KNF MCP Server

by Kymylyy
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript

get_registry_stats

Counts entities in the Polish KNF e-RUP payment institution registry based on filters like name, NIP, status, or entity type.

Instructions

Return only the count of entities matching optional filters.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "get_registry_stats"
  }
}

Input Schema

NameRequiredDescriptionDefault
nameNo
nipNo
knf_numberNo
entity_typeNo
statusNo
cityNo
date_fromNo
date_toNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.9/5.0
Behavior2/5

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

With no annotations provided, the description carries full burden for behavioral disclosure. It only states the return value (count) but omits details like whether the count is approximate, any performance implications, or that it's a lightweight read operation.

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 a single sentence with no extraneous words, achieving high conciseness. However, it is under-specified, sacrificing completeness for brevity.

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 8 optional parameters, no output schema, and no annotations, the description is too minimal. It fails to provide context on date formats, allowed values for free-text parameters, or the structure of the response, leaving the agent with significant uncertainty.

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 description must compensate, but it only generically mentions 'optional filters' without explaining individual parameters. The schema lists 8 parameters, and their meanings are left entirely to the agent to infer from names.

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 it returns only a count of entities matching optional filters, which distinguishes it from sibling tools that return full entity details. However, it doesn't specify what 'registry' refers to, but context from sibling names makes it clear.

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 use when only a count is needed, but it doesn't explicitly mention when not to use it or provide alternatives. Sibling tools like search_entities could be for full lists, but no guidance is given.

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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