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Glama

Norges Bank

by io.github.pipeworx-io

Get Exchange Rate

get_exchange_rate
Read-onlyIdempotent

Latest (or last N) Norges Bank exchange rate for a currency against the Norwegian krone (NOK). The value is how many NOK one unit of the base currency buys (e.g. USD → ~9.25 NOK). Builds the EXR series key B.{CURRENCY}.NOK.SP (business-day spot). currency is the ISO 4217 code, e.g. "USD", "EUR", "GBP", "SEK", "JPY".

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
last_nNoReturn only the last N observations (default 1).
currencyYesISO 4217 base currency code (USD, EUR, GBP, SEK, ...).
end_periodNoEnd date (YYYY-MM-DD).
start_periodNoStart date (YYYY-MM-DD). Overrides last_n if set.

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: +[
+  {
+    "currency": "USD"
+  },
+  {
+    "currency": "EUR",
+    "last_n": 5
+  },
+  {
+    "currency": "GBP",
+    "end_period": "2024-12-31",
+    "start_period": "2024-01-01"
+  }
+]
  2. First observed

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already indicate read-only, idempotent, and non-destructive behavior. The description adds useful context beyond annotations: the series key format (B.{CURRENCY}.NOK.SP), business-day spot meaning, and the value interpretation (NOK per unit). No contradictions.

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 concise (two sentences) and well-structured, opening with the primary function followed by key details and examples. Every sentence earns its place without unnecessary fluff.

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

Completeness4/5

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

Given the tool's simplicity, a read-only lookup with fully covered parameters and no output schema, the description provides sufficient context: the meaning of the value, series key, and examples. It could mention handling of missing dates or other edge cases, but that is not critical for basic usage.

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 covers all parameters with descriptions (100% coverage), so the baseline is 3. The description adds extra semantic value by explaining the currency code examples and the series key, which helps clarify the purpose of the currency parameter and enhances understanding of last_n and period behavior.

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's purpose: fetching the latest (or last N) Norges Bank exchange rate for a currency against NOK. It names the specific resource (Norges Bank EXR series) and explains the value interpretation, effectively distinguishing it from generic series 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 this tool (for NOK exchange rate queries) and includes examples of currencies. It does not explicitly mention alternatives or exclusions, but the purpose is specific enough that an agent would not confuse it with sibling tools.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All Norges Bank toolsInspect
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TDQS

A3.9/5.0
Disambiguation4/5

Most tools have distinct purposes (e.g., entity_profile vs compare_entities), but there is some overlap between ask_pipeworx, ask_pipeworx_grounded, and deep_research, as well as among polymarket tools, which could cause misselection.

Naming Consistency2/5

Tool names are inconsistent, mixing verb_noun (list_flows, get_series) with descriptive names (ask_pipeworx, bet_research) and varying conventions (snake_case vs no underscores).

Tool Count3/5

33 tools is on the high side but manageable for a broad platform; however, the server name 'Norges Bank' suggests a narrower scope, making the count feel bloated.

Completeness2/5

For a server named 'Norges Bank', many tools are irrelevant (polymarket, pipeworx meta-tools, memory, etc.), leaving significant gaps in core Norwegian banking data coverage.

Resources