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Lextiva Compliance MCP Server

Lextiva Compliance MCP Server

by arturayupov
OverviewSchemaSourceRelated ServersDiscussionsAdmin
JavaScript
Hybrid

get_data_subject_right

Retrieve the full record for a data subject right, such as erasure or portability, by passing its identifier.

Instructions

Returns the full record for a single data subject right. Pass ids like 'erasure', 'portability', 'opt_out_sale_or_sharing'.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "id": "<id>"
    },
    "name": "get_data_subject_right"
  }
}

Input Schema

NameRequiredDescriptionDefault
idYesData subject right id (e.g. 'erasure', 'portability')

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.1.0

TDQS

A3.9/5.0
Behavior3/5

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

The description says 'Returns the full record' but does not detail what the record contains, error behavior for invalid ids, or any side effects. Given no annotations, this is basic but sufficient for a simple read operation.

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?

Two concise sentences with no extraneous information. The description is front-loaded with the core purpose and follows with helpful examples.

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

Completeness3/5

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

Lacks details on return structure, error handling, or any prerequisites. For a tool with no output schema and no annotations, the description is somewhat sparse but covers the essential purpose.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so parameter info is already clear. The description adds value by providing example parameter values ('erasure', 'portability'), enhancing usability beyond the schema.

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 returns the full record for a single data subject right, including example ids like 'erasure' and 'portability'. This leaves no ambiguity about the tool's function.

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?

No explicit guidance on when to use this tool versus siblings like list_data_subject_rights or compliance_checklist. Usage is implied but not differentiated, which is adequate but not exemplary.

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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