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mcp-knowledge

by io.github.getgapup

ftg_sourcing_buyers

Read-only

Return verified local buyers in a country — companies sourcing a given commodity, with buyer type, city, website, annual volume range and certification requirements. When to use this tool: an agent builds a sourcing or export shortlist, or needs real B2B demand contacts in a market. Input: a country and an optional commodity filter.

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.
limitNoMaximum buyers to return (default 20)
countryYesCountry ISO-2 code or name
commodityNoOptional commodity slug to filter buyers by

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
buyersYes
countryYes
commodityNo
buyer_countYes

TDQS

A4/5.0
Behavior3/5

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

Annotations (readOnlyHint: true, openWorldHint: true) already indicate safe read behavior and dynamic data. The description adds that it returns verified buyers with specific fields but does not discuss edge cases, response format, or async behavior (covered by schema). It is adequate but not rich.

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 with a separate usage guideline and input note. It is front-loaded with the main output, no fluff, and efficiently communicates purpose and use case.

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 output schema exists, the description covers the main purpose, use case, input, and key returned fields. It does not mention pagination or async behavior, but these are in the schema. Slight gap in explaining the openWorldHint implication.

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 clear parameter descriptions. The description reinforces country and commodity but does not add meaning beyond the schema for async or limit. Baseline 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 'verified local buyers in a country' with specific details like buyer type, city, website, etc. It distinguishes itself from sibling ftg_* tools (e.g., ftg_seller_catalog, ftg_investor_directory) by focusing on buyers for sourcing/export shortlisting.

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 explicitly says 'When to use this tool: an agent builds a sourcing or export shortlist, or needs real B2B demand contacts.' It provides clear context but does not mention when not to use it or alternatives, though the sibling list implies differentiation.

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

C2.8/5.0
Disambiguation2/5

Many tools have overlapping purposes, especially in competitive intelligence, ESG, and risk assessment. For example, there are multiple tools for competitor analysis (competitive_deep_dive, competitor_intel, competitor_moves, etc.) with unclear boundaries. Agents would struggle to select the correct tool without deep understanding of subtle differences.

Naming Consistency2/5

Tool names are a mix of English and French, and follow no consistent pattern. Some use snake_case (e.g., abm_architect, action_plan_esg), while others are verb-focused (e.g., content_catalog, fx_rate). The lack of a uniform naming convention makes it hard for agents to predict tool names.

Tool Count1/5

With 271 tools, the server is excessively large. Even for a broad knowledge domain, this number of tools makes discovery and selection inefficient. Typical coherent servers have 3-15 tools; this has an order of magnitude more, indicating poor scoping.

Completeness3/5

The tool set covers many domains (compliance, finance, marketing, HR, etc.), but the coverage is uneven due to redundancy. Key areas have multiple overlapping tools, while some sub-domains may still have gaps. Overall, the surface is broad but not well-curated.

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