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adog0822

@loxeai/mcp-server

by adog0822

Export scan results as NIST OSCAL assessment-results

export_oscal
Read-onlyIdempotent

Convert a completed scan into a NIST OSCAL assessment-results JSON document for GRC platforms. Emits only not-satisfied findings and returns the document as a string, without writing files.

Instructions

Emits the scan as a NIST OSCAL assessment-results document (JSON), the machine-readable format used by GRC platforms and assessment tooling. Returned as a STRING; this server writes no files. Two deliberate limitations are stated inside the document itself: no official OSCAL catalog for SOC 2 exists, so criterion IDs are used descriptively; and only 'not-satisfied' findings are ever emitted — this tool never asserts 'satisfied', because the absence of a scanner finding is not evidence that a criterion is met.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
batchIdYesBatch ID returned by scan_iac

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
bytesYesSize of the OSCAL JSON, which is returned in `content`, not here.
oscalVersionYes
findingsEmittedYesOnly ever not-satisfied findings. 'satisfied' is never emitted.
suggestedFilenameYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.1.0

TDQS

A4.3/5.0
Behavior5/5

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

The description goes well beyond the readOnlyHint/idempotentHint annotations by disclosing that the result is a STRING, that the server writes no files, and that the document contains deliberate limitations: descriptive criterion IDs due to no SOC 2 catalog, and only 'not-satisfied' findings emitted. These are non-obvious, decision-relevant behaviors.

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 sentences with no filler: the first states the core action and format, the second covers return type and side effects, and the third explains the two key limitations. Each sentence earns its place and the most important information is front-loaded.

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?

For a one-parameter, read-only, idempotent export tool with a full input schema and an output schema, this description covers every behavioral nuance an agent needs: return type, file effects, and embedded limitations. Nothing material is missing.

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 description coverage is 100% and the single parameter batchId is already documented as 'Batch ID returned by scan_iac,' so the description does not need to add parameter-level detail. The baseline of 3 applies because the schema carries the semantic weight and the description adds no further parameter context.

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 names a specific verb ('Emits') and a precise resource ('NIST OSCAL assessment-results document (JSON)'), with a clear format and purpose. The machine-readable GRC orientation implicitly differentiates it from human-readable siblings like render_trust_page and preview_trust_page, so an agent can tell them apart.

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 gives useful context about the output being machine-readable for GRC platforms and assessment tooling, so an agent can infer this is for integrations rather than human review. However, it never explicitly states when to use this tool versus alternatives, nor does it mention any exclusion criteria.

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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