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ftg_seller_catalog

Read-only

Return seller catalogues registered on FTG — exporters and producers with their commodity, monthly capacity, certifications and target export markets. When to use this tool: an agent builds a supplier or sourcing shortlist. Input: optional seller country and commodity.

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.
limitNo
countryNoOptional seller country ISO code or name
commodityNoOptional commodity filter

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
countYes
sellersYes

TDQS

A4.2/5.0
Behavior4/5

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

Annotations include readOnlyHint=true, and the description aligns with this, describing a read operation. It adds behavioral context by listing the kind of information returned (monthly capacity, certifications, target markets). It does not discuss async behavior or pagination, but the async param is described in the schema and an output schema exists.

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 two sentences and an input clause—all information is front-loaded and every part earns its place. It succinctly states purpose, content, use case, and inputs without redundancy.

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 (read-only catalog with optional filters, output schema present, annotations provided), the description is mostly complete. It covers what, when, and input. It does not mention the async option or limit, but those are fully specified in the schema, so the description is adequate.

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 75% (async, country, commodity have descriptions; limit does not). The description highlights 'optional seller country and commodity' which aligns with schema descriptions, but adds no extra meaning for limit or async. With high schema coverage, a 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 clearly states the tool returns seller catalogues with specific content (commodity, capacity, certifications, markets), using a specific verb 'Return'. It also provides the use case ('builds a supplier or sourcing shortlist'), which distinguishes it from siblings like ftg_sourcing_buyers.

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?

Explicitly states when to use the tool: 'an agent builds a supplier or sourcing shortlist.' It does not explicitly mention when not to use it or reference alternatives, but the context is clear and actionable.

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.