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shadoprizm

Cyber Lens AI MCP Server

by shadoprizm

get_scan_results

Retrieve detailed security scan findings, including severity scores, vulnerability lists, CWE classifications, and remediation guidance for a completed scan.

Instructions

Retrieve detailed findings from a completed security scan.

Returns:

  • Overall security score (0-100)

  • List of vulnerabilities with severity levels

  • CWE classifications

  • Specific recommendations for each finding

  • CVE references where applicable

  • Remediation guidance links

Use this after initiating a full cloud scan with scan_website or scan_repository. Local quick website scans return findings immediately and do not produce a scan ID. If no account is connected yet, the MCP server will connect first and then retrieve the cloud scan result.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
scan_idYesThe scan ID returned from scan initiation
severity_filterNoFilter results by severity levelall
Behavior4/5

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

No annotations are present, so the description carries the behavioral disclosure burden. It does well by revealing that the server will auto-connect an account first, that local scans are not eligible, and that this is for completed cloud scans. It could add more about failure modes or scan completion status, but the provided behavior is clearly disclosed.

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 purpose is front-loaded and the return-value bullets are structured for easy scanning. The description is longer than strictly necessary, but each section earns its place, especially given the lack of an output schema.

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

Completeness5/5

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

With no output schema and no annotations, the description fully compensates by enumerating return contents, clarifying eligibility, and explaining the account-connect behavior. An agent has enough context to decide when to call it and what to expect from the response.

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 restates that scan_id comes from scan initiation and that severity_filter filters by severity, but it does not add deeper parameter meaning beyond the schema. The schema already documents defaults and allowed values, so the description adds limited extra semantic value.

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 opens with a specific action and resource: 'Retrieve detailed findings from a completed security scan.' The return-value list makes clear this is the full-findings tool rather than get_security_score (score only) or get_remediation_guide (guidance only), so it differentiates well from siblings.

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

Usage Guidelines5/5

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

It explicitly states when to use the tool: 'after initiating a full cloud scan with scan_website or scan_repository.' It also gives an exclusion — local quick scans do not produce a scan ID — and explains what happens when no account is connected. This is direct, actionable usage guidance.

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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