gapup-mcp

vuln_patch_priority_engine

Read-onlyIdempotent

As a CTO, quickly prioritize unpatched CVEs by combining exploitability scores (EPSS) with cloud asset criticality. Input a list of CVE IDs and your AWS service types (e.g., EC2, RDS) to receive a ranked patching order with risk scores and estimated cloud impact. Uses public NVD, OpenCVE, and AWS pricing data. Ideal for vulnerability management and cloud security posture improvement.

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.
`cveIds`	Yes	List of CVE identifiers to analyze (e.g., ["CVE-2021-44228", "CVE-2023-3824"])
`maxResults`	No	Maximum number of prioritized CVEs to return (default: 10)
`awsServices`	No	AWS service types affected by these CVEs (e.g., ["EC2", "RDS", "Lambda"])

Output Schema

TableJSON Schema

Name	Required	Description	Default
`status`	Yes
`sources`	No
`warnings`	No
`prioritizedCves`	No

TDQS

A4.2/5.0

Behavior4/5

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

Annotations already indicate readOnly and idempotent. Description adds value by disclosing data sources (NVD, OpenCVE, AWS pricing) and async behavior. No contradictions.

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?

Three well-structured sentences. Front-loaded with purpose, followed by output and context. No filler.

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?

With an output schema (not shown), the description provides sufficient context for inputs and processing. Lacks specifics on scoring methodology but overall adequate for a read-only tool.

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 covers all 4 parameters with descriptions (100% coverage). Description restates inputs but does not add new semantic details beyond what the schema already provides.

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 it 'prioritizes unpatched CVEs by combining exploitability scores (EPSS) with cloud asset criticality.' It specifies inputs and outputs, and its role is distinct from siblings like cve_security_lookup or vuln_exploitability_forecast.

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 targets vulnerability management and cloud security posture improvement. It implies when to use (quick prioritization) but does not provide explicit when-not-to-use or compare with alternatives.

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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