gapup-mcp

africa_trade_finance_esg_rater

Read-onlyIdempotent

As a COO, evaluate ESG compliance of African trade finance providers using World Bank WITS trade statistics and CDP climate disclosure data. Input the financial institution's name or identifier, and receive an ESG rating with breakdown across environmental, social, and governance dimensions. Ideal for due diligence on trade partners or portfolio risk assessment. Pass async:true to avoid timeout.

Input Schema

TableJSON Schema

Name	Required	Description
`year`	No	Assessment year (2018-2023)
`async`	No	If 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.
`countryCode`	No	ISO 2-letter country code (e.g., 'ZA' for South Africa)
`institutionName`	Yes	Full name of the trade finance provider (e.g., 'Standard Bank Group')

Output Schema

TableJSON Schema

Name	Required	Description
`status`	Yes
`sources`	Yes
`warnings`	Yes
`esgRating`	Yes
`socialScore`	No
`tradeVolume`	No	Annual trade finance volume (USD)
`carbonIntensity`	No	CO2 emissions per million USD financed (tons)
`governanceScore`	No
`environmentalScore`	No

TDQS

A4.1/5.0

Behavior4/5

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

Annotations indicate readOnly, openWorld, and idempotent hints. The description adds value by noting the 'async' parameter to avoid timeouts, which is a behavioral trait not covered by annotations. No contradiction.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is relatively concise at two sentences plus an async note, but it could be better structured with bullet points or clearer separation of purpose vs. usage. Still efficient.

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 has an output schema and 4 parameters, the description provides context on data sources and use cases. It adequately covers the core function, though more detail on output structure or parameter relationships could help.

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

Parameters4/5

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

Schema coverage is 100%, providing baseline of 3. The description adds meaning to the 'async' parameter with usage guidance and reiterates the primary input (institution name), improving understanding beyond the schema.

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 evaluates ESG compliance of African trade finance providers using specific data sources (World Bank WITS, CDP) and returns an ESG rating with dimensional breakdown. It distinguishes itself from siblings by its geographic and sector focus.

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?

The description mentions ideal use cases ('due diligence on trade partners or portfolio risk assessment') but does not explicitly state when to avoid this tool or mention alternative tools for similar tasks, leaving ambiguity.

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

C2.5/5.0

Disambiguation2/5

With 271 tools, many have overlapping purposes (e.g., multiple competitor intel tools, multiple financial modelers, multiple ESG auditors). Detailed descriptions help slightly, but the sheer volume creates confusion. Agents would struggle to select the right tool among many similar options.

Naming Consistency1/5

Tool names are wildly inconsistent: mix of English and French, snake_case and short phrases, some very generic (process, run, execute equivalents). No discernible naming convention (e.g., abm_architect vs. boundary_control vs. bp_narratif). This makes it hard to predict tool names.

Tool Count1/5

271 tools is far beyond typical well-scoped servers (3-15). This indicates an unfocused, over-bloated tool surface. Even for a general business intelligence server, this number is excessive and violates the principle of each tool earning its place.

Completeness2/5

Despite the large count, coverage feels scattered. Some domains (e.g., content, competitive intel) have many tools, while others (e.g., supply chain, HR) have gaps. The set lacks a coherent scope; it seems like a dump of many separate tool collections rather than a complete, curated surface.

Resources

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