Skip to main content
Glama

gapup-mcp

by io.github.getgapup

agoa_eba_intelligence

Read-only

Intelligence préférentielle AGOA (US→Africa) et EBA/GSP (EU→Africa). Vérifie l'éligibilité d'un pays africain aux programmes tarifaires préférentiels, l'éligibilité d'un produit par code HS, identifie les meilleures opportunités d'export Afrique→US/EU, et fournit les règles de conformité (rules of origin, valeur ajoutée, docs). Différenciateur Africa diaspora : 39 pays AGOA + 47 LDCs EBA encodés. Sources : AGOA.info · EU EBA · EU GSP+ · WTO Tariff · UN Comtrade.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modeYesMode d'analyse : 'country_eligibility' (statut AGOA/EBA/GSP d'un pays africain) | 'product_eligibility' (éligibilité d'un produit par code HS) | 'trade_opportunity' (top opportunités export Afrique→US/EU) | 'compliance_check' (rules of origin, seuils valeur ajoutée, documentation)
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.
hs_codeNoCode HS (Harmonized System) 6+ chiffres (requis pour product_eligibility). Exemple : '620342' = pantalons coton homme, '090111' = café arabica non torréfié, '060310' = fleurs fraîches.
country_isoNoCode ISO 2-lettres du pays africain (requis pour country_eligibility). Exemples : KE=Kenya, NG=Nigeria, ZA=Afrique du Sud, ET=Éthiopie, LS=Lesotho, GH=Ghana.
destinationNoMarché de destination pour trade_opportunity : 'US', 'EU', ou 'both' (défaut). Ignoré pour les autres modes.

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare the tool read-only and open-world. The description adds valuable behavioral context by listing data sources (AGOA.info, EU EBA, etc.) and emphasizing the tool's encoded country coverage, which informs the agent about data provenance and scope. No contradictions with 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 three sentences long, front-loaded with the primary purpose, and includes only high-value information: the four modes, coverage differentiator, and data sources. Every sentence earns its place, with no redundancy.

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?

For a multi-mode tool with five parameters and no output schema, the description is thorough. It covers all modes, indicates the Africa→US/EU scope, highlights unique country coverage, and cites sources. The schema handles parameter requirements, so the description is complete enough for an agent to select and invoke the tool correctly.

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?

The input schema provides 100% coverage with descriptions and examples for all five parameters, including enum options and required conditions. The description itself does not add significant parameter-level details beyond reiterating the tool's functionalities, so the baseline of 3 is appropriate.

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 uses specific verbs (vérifie, identifie, fournit) and clearly defines the tool's resource: AGOA/EBA/GSP preferential trade intelligence for Africa–US/EU trade. It distinguishes itself from siblings by its unique coverage of 39 AGOA countries and 47 EBA LDCs, making the purpose unmistakable.

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 usage context by enumerating four modes (country eligibility, product eligibility, trade opportunities, compliance) and the geographic scope. It does not explicitly name alternative tools or state when not to use it, but the context is strong enough for an agent to infer appropriate use cases.

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

All gapup-mcp toolsInspect
Try in Browser
RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

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.

Resources