gapup-mcp

vuln_exploitability_forecast

Read-onlyIdempotent

As a CTO, assess the exploitability risk of CVEs using EPSS scores and cloud asset exposure data. Input a CVE ID (e.g., CVE-2021-44228) to receive exploitability likelihood, affected cloud services, and threat intelligence context. Returns structured risk metrics for prioritization. Sources: CVE NVD, OpenCVE, GitHub Advisories. Pass async:true to avoid timeout.

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.
`cveId`	Yes
`cloudProvider`	No
`includeDetails`	No

Output Schema

TableJSON Schema

Name	Required	Description	Default
`cveId`	Yes
`status`	Yes
`sources`	Yes
`warnings`	Yes
`epssScore`	No
`lastUpdated`	No
`cloudExposure`	No
`epssPercentile`	No

TDQS

A3.7/5.0

Behavior4/5

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

Annotations already declare readOnlyHint, openWorldHint, and idempotentHint, so the safety profile is clear. The description adds valuable behavioral context: data sources (CVE NVD, OpenCVE, GitHub Advisories), output type (structured risk metrics), and a warning about potential timeouts with async usage. No contradictions with annotations.

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?

Description is concise (two sentences plus a list of sources and an async note). It is front-loaded with the purpose. Every sentence adds value: purpose, required input, output description, sources, and key behavioral hint. Could be slightly more structured (e.g., bullet points) but effectively communicates without verbosity.

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 annotations (readOnlyHint, idempotentHint) and an output schema (not shown but present), the description adequately covers purpose, sources, input hints, and async behavior. It does not explain all parameters or output format in detail, but the output schema fills that gap. The description is fairly complete for a tool with these structured supports.

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 low (25%), with only 'async' having a description in the schema. The description explains 'cveId' (input a CVE ID) and 'async' (pass true to avoid timeout) but does not mention 'cloudProvider' or 'includeDetails'. While it compensates for two key parameters, the missing explanation for the other two leaves gaps. Baseline 3 is appropriate given the partial compensation.

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?

Description clearly states the tool assesses exploitability risk of CVEs using EPSS scores and cloud exposure data. It identifies a specific verb ('assess'), resource ('CVE exploitability'), and differentiates from sibling tools like cve_security_lookup and vuln_patch_priority_engine by focusing on exploitability forecasting with cloud context.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No explicit guidance on when to use this tool versus alternatives. The description implies it's for exploitability risk with cloud data but does not mention when-not to use it or provide comparisons to similar tools like cve_security_lookup or vuln_patch_priority_engine. The note about async is invocation advice, not usage 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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