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gapup-mcp

by io.github.getgapup

attack_surface_monitor

Read-only

Surveillance surface d'attaque — Gapup agent-payable C-suite expertise (RISK). Returns a structured, audited deliverable. Answers: Which Internet-facing assets of combine a critical CVE, an exposed service, and no WAF — top findings to fix in 14 days? · What is the attack surface of : subdomains, open ports, SSL/TLS grades, and associated CVEs? · Give me a CISO-ready ASM report with blast radius estimate and SLA-driven remediation plan for . · What is the email phishing risk for ? Assess SPF/DMARC posture and recommend improvements. · During M&A due diligence, what are the top cyber exposures on 's Internet-facing infrastructure? Reference case: Velora Payments — 8 assets exposés · 2 critiques (CVE-2023-44487 HTTP/2 RapidReset, Admin panel ouvert) · . Inputs are validated server-side — send the documented case fields.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
asyncNoIf 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.
focusNo
domainYes
exclusionsNo
scope_cidrsNo
include_email_surfaceYes

TDQS

B3.1/5.0
Behavior3/5

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

Annotations already declare readOnly and openWorld. The description adds that returns a structured, audited deliverable and gives reference example, but does not disclose performance characteristics, rate limits, or other behavioral details. With annotations providing safety profile, this is adequate but not exceptional.

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

Conciseness2/5

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

The description is a long, unstructured paragraph with promotional elements like 'Gapup agent-payable C-suite expertise' and a reference case that doesn't aid tool selection. It would benefit from a concise summary and structured capabilities list.

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?

Without an output schema, the description fails to explain the output structure beyond 'structured, audited deliverable'. It also doesn't clarify the meaning of exclusions/scope_cidrs or the async workflow, making it incomplete for a 6-parameter tool.

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 (only async has a description). The description implicitly covers domain and include_email_surface via examples, but leaves focus, exclusions, scope_cidrs, and async unexplained. This is insufficient compensation for the low schema coverage.

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 this tool monitors attack surface of a domain, answering specific security questions (CVEs, exposed services, WAF, subdomains, ports, SSL/TLS, email phishing). It is specific to attack surface monitoring, though it doesn't explicitly distinguish itself from sibling tools like cve_security_lookup or email_domain_health_check.

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?

Example user queries provide clear context for when to use the tool: for ASM assessments, CISO reports, email phishing risk, and M&A due diligence. However, it doesn't mention exclusions or when not to use this tool versus 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

C2.4/5.0
Disambiguation1/5

Over 50 tools share the identical template 'Gapup agent-payable C-suite expertise' with similar French descriptions and reference cases, making their boundaries indistinguishable. Clusters like competitor_intel, competitive_deep_dive, competitor_moves, competitor_profiles, competitor_pricing_radar, competitor_pricing_scrape, and competitor_recommendations heavily overlap in purpose.

Naming Consistency1/5

Names are chaotic: mix of French and English, snake_case and camelCase, verb_noun, noun, and adjective forms with no uniform pattern. Examples like 'bp_narratif', 'content_enrichment', 'ai_governance_full_report_async', and 'job_result' show no coherent naming convention.

Tool Count1/5

271 tools is far beyond any reasonable MCP server scope, creating an overwhelming selection burden for agents. This count vastly exceeds the 25+ threshold for 'too many' and makes navigation impractical.

Completeness2/5

While the server covers many business domains, it lacks lifecycle operations (e.g., no update/delete tools for the deliverables it generates) and the input specifications are vague ('documented case fields' without documentation), creating functional dead ends. The sheer breadth does not compensate for these gaps.

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