gapup-mcp

industry_classifier_naics_sic

Read-only

Classificateur d'industrie NAICS/SIC/NACE — Gapup agent-payable C-suite expertise (CMO). Returns a structured, audited deliverable. Answers: What is the NAICS code for a company that does ? · Give me NAICS + SIC + NACE classification for this company description. · Which industry sector (GICS) does this company belong to for equity analysis? · What HS code applies to products manufactured by this company? · For EU procurement compliance, what NACE Rev. 2 code applies to this company? · Classify this business into NAICS + SIC + ISIC + GICS + NACE + HS with hierarchy and confidence. · I need to segment my ICP list by NAICS 4-digit subsector — classify these company descriptions. Reference case: Helios Cold Chain EU — Freight forwarding maritime réfrigéré · . Inputs are validated server-side — send the documented case fields.

Input Schema

TableJSON Schema

Name	Required	Description
`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.
`company_url`	No
`company_name`	No
`company_description`	Yes
`focus_classifications`	No
`primary_revenue_source`	No

TDQS

C2.8/5.0

Behavior2/5

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

Annotations already declare readOnlyHint and openWorldHint. The description adds minimal behavioral context beyond mentioning server-side validation and that it returns a structured deliverable. No significant additional disclosure.

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

Conciseness3/5

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

The description is somewhat verbose with many example questions, but the core purpose is front-loaded. It could be more concise without losing clarity.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a complex tool with 6 parameters and no output schema, the description is incomplete. It does not explain return format, error handling, or how to interpret results beyond 'structured, audited deliverable'.

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

Parameters2/5

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

Schema description coverage is low (17%). The description does not provide meaningful explanations of parameters beyond listing example queries. Key parameters like focus_classifications are not elaborated.

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 classifies companies into NAICS/SIC/NACE and returns a structured deliverable, with example queries. However, it does not explicitly differentiate from sibling tools, which are numerous but this one seems unique.

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 implies usage for any company description to get industry codes but lacks explicit when-to-use or when-not-to-use guidance, and no alternatives are mentioned.

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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