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gapup-mcp

by io.github.getgapup

supply_chain_fx_exposure_dashboard

Read-onlyIdempotent

Provides real-time foreign exchange exposure dashboard for supply chain monitoring. Designed for COO persona to track currency risk across suppliers and regions. Inputs include supplier IDs, base currency, and target currencies. Outputs structured FX exposure data with risk indicators, exchange rates, and supplier impact analysis sourced from World Bank LPI and live FX rate APIs.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
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.
supplierIdsNoList of supplier identifiers to analyze
baseCurrencyYesBase currency code (ISO 4217) for exposure calculation
riskThresholdNoPercentage threshold for high-risk exposure flagging
targetCurrenciesYesTarget currency codes (ISO 4217) to compare against base

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataNo
statusYes
sourcesNo
warningsNo

TDQS

A3.8/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, openWorldHint, and idempotentHint. The description adds useful context about real-time behavior, data sources (World Bank LPI and live FX APIs), and output contents (risk indicators, exchange rates, supplier impact analysis), exceeding the baseline set by annotations without contradicting them.

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 with three sentences: purpose, persona/use case, and input/output summary. It is front-loaded with the primary function and contains no redundant information.

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 presence of an output schema, rich annotations, and 100% parameter coverage, the description provides sufficient context about the tool's purpose, data sources, and output format. It does not address potential edge cases or usage caveats, but these are adequately covered by structured fields.

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 description coverage is 100%, so the parameter semantics baseline is 3. The description merely repeats that inputs include supplier IDs, base currency, and target currencies without adding extra meaning or details beyond the schema's own descriptions.

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 provides a real-time FX exposure dashboard for supply chain monitoring, with a specific verb ('Provides') and resource ('dashboard'). It distinguishes itself from simpler FX rate tools by mentioning supply chain context and risk indicators, but does not explicitly name alternative tools.

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?

Usage context is implied through 'Designed for COO persona to track currency risk across suppliers and regions', but there is no explicit guidance on when to use this tool versus alternatives like fx_rate or working_capital_fx_hedge_optimizer. No exclusions or alternative references are provided.

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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