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gapup-mcp

by io.github.getgapup

fx_rate

Read-only

Get the current or historical foreign-exchange rate for any currency pair — the exact exchange rate, FX rate or conversion rate an agent needs to convert a currency amount or feed a finance, trading, invoicing or pricing workflow. Covers EUR/USD, USD/JPY, GBP/EUR and every ISO-4217 currency pair. Returns the latest spot rate, or a historical rate by date. Use when a workflow needs a precise live or past currency exchange rate, or to convert money between two currencies. Source: European Central Bank reference rates via Frankfurter. Inputs: from/to ISO-4217 currency codes, optional date (YYYY-MM-DD).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
toYesQuote currency, ISO-4217 (e.g. USD)
dateNoOptional YYYY-MM-DD for a historical rate
fromYesBase currency, ISO-4217 (e.g. EUR)
asyncNoIf true, returns a job_id immediately (<200ms) instead of waiting for the result. Poll the result with job_result(job_id). Use for slow tools to avoid client timeouts.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
toYes
fromYes
rateYes
as_ofYes
sourceYes
source_urlNo

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already flag readOnlyHint=true and openWorldHint=true. The description adds meaningful behavioral context: the data source (European Central Bank via Frankfurter), return behavior (latest spot or historical), and coverage ('every ISO-4217 currency pair'). It doesn't mention limitations like non-trading days, but the added context is valuable beyond annotations.

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 a single well-organized paragraph where each phrase earns its place: purpose, examples, coverage, return type, usage trigger, data source, and inputs. It front-loads the verb and avoids filler, making it easily scannable.

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 the tool's simplicity, an output schema is present (so return values need no explanation), and schema covers all parameters. The description competently addresses scope, source, use cases, and input format. It does not explicitly mention asynchronous execution, but that is in the schema, so no gap exists.

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

Parameters3/5

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

Schema coverage is 100% with descriptions for from/to/date/async already provided. The description only restates the input codes and the date format (YYYY-MM-DD), which are already in the schema. It adds no new semantic detail beyond what's structured, so baseline 3 applies.

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 opens with 'Get the current or historical foreign-exchange rate for any currency pair', a specific verb+resource combination that clearly identifies the tool's function. It distinguishes itself from siblings like interest_rate or historical_price_series by explicitly mentioning 'FX rate' and 'ISO-4217 currency pair'.

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?

It provides explicit usage guidance: 'Use when a workflow needs a precise live or past currency exchange rate, or to convert money between two currencies.' While it doesn't name alternatives, the domain is self-evident and the conditions are clear.

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

C2.4/5.0
Disambiguation1/5

Over 50 tools share the identical template 'Gapup agent-payable C-suite expertise' with similar French descriptions and reference cases, making their boundaries indistinguishable. Clusters like competitor_intel, competitive_deep_dive, competitor_moves, competitor_profiles, competitor_pricing_radar, competitor_pricing_scrape, and competitor_recommendations heavily overlap in purpose.

Naming Consistency1/5

Names are chaotic: mix of French and English, snake_case and camelCase, verb_noun, noun, and adjective forms with no uniform pattern. Examples like 'bp_narratif', 'content_enrichment', 'ai_governance_full_report_async', and 'job_result' show no coherent naming convention.

Tool Count1/5

271 tools is far beyond any reasonable MCP server scope, creating an overwhelming selection burden for agents. This count vastly exceeds the 25+ threshold for 'too many' and makes navigation impractical.

Completeness2/5

While the server covers many business domains, it lacks lifecycle operations (e.g., no update/delete tools for the deliverables it generates) and the input specifications are vague ('documented case fields' without documentation), creating functional dead ends. The sheer breadth does not compensate for these gaps.

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