gapup-mcp

manufacturing_esg_compliance_mapper

Read-onlyIdempotent

As a COO, quickly identify ESG compliance gaps across manufacturing facilities using EPA TRI emissions data and GRI sustainability standards. Input facility identifiers or geographic regions to receive a prioritized remediation roadmap with risk scores, regulatory violations, and suggested corrective actions. Ideal for sustainability reporting, regulatory risk assessment, and operational improvement planning. Keywords: ESG compliance, manufacturing facilities, EPA TRI, GRI standards, sustainability reporting, regulatory risk.

Input Schema

TableJSON Schema

Name	Required	Description
`year`	No	Reporting year (default: current year - 1)
`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.
`region`	No	Geographic region (state, county, or ZIP code) for facility search
`includeGri`	No	Include GRI standards analysis (default: true)
`facilityIds`	Yes	List of EPA facility identifiers (e.g., TRIFID)

Output Schema

TableJSON Schema

Name	Required	Description	Default
`status`	Yes
`sources`	Yes
`summary`	No
`warnings`	Yes
`facilities`	Yes

TDQS

A3.5/5.0

Behavior3/5

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

Annotations already declare readOnlyHint, openWorldHint, and idempotentHint, so the description's burden is reduced. The description adds context about using EPA TRI and GRI data and producing a roadmap, but it does not mention the async parameter or potential latency, which is a significant behavioral aspect given the async option in the schema.

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 concise with two sentences and a keyword list. It front-loads the target user (COO) and action. The keywords add searchability but slightly clutter. Overall, it is well-structured and succinct.

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 complexity (ESG compliance with multiple data sources) and the presence of an output schema, the description is fairly complete. It covers data sources, inputs, and outputs. However, it could mention that results may be large or require polling via the async parameter for better completeness.

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%, so the baseline is 3. The description adds minimal meaning beyond the schema—it mentions facility identifiers and regions but does not provide additional context for parameters like year or async. The schema descriptions already adequately explain each parameter.

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 identifies the tool's purpose: identifying ESG compliance gaps across manufacturing facilities using EPA TRI and GRI standards. It specifies inputs (facility IDs or regions) and outputs (prioritized remediation roadmap). However, it does not explicitly differentiate from sibling tools like esg_audit_multi or supplier_esg_audit, which may have overlapping functionality.

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 COOs in sustainability reporting and regulatory risk assessment, but it does not provide explicit guidance on when to use this tool versus alternatives (e.g., esg_audit_multi for broader audits). No exclusions or when-not-to-use are stated, leaving the agent to infer context.

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.

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