gapup-mcp

lgpd_data_subject_rights_automator

Read-onlyIdempotent

Automates LGPD Data Subject Access Requests (DSARs) for legal teams, handling Brazil-specific data retention, erasure, and access workflows. Accepts user identifiers, request type (access/rectification/deletion), and optional scope filters. Returns structured response with compliance status, warnings, and source references to Brazilian LGPD and CNIL decisions.

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.
`scope`	No	Optional list of data categories to limit the request
`urgency`	No	Priority level for processing
`requestType`	Yes	Type of LGPD request
`userIdentifier`	Yes	CPF, email, or other unique identifier for the data subject

Output Schema

TableJSON Schema

Name	Required	Description	Default
`status`	Yes
`sources`	No
`warnings`	No
`dataCategories`	No
`erasureDeadline`	No
`complianceStatus`	No
`retentionPeriodDays`	No

TDQS

B3.2/5.0

Behavior1/5

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

Annotations declare readOnlyHint=true, idempotentHint=true, but the description mentions handling erasure and deletion, which contradicts read-only semantics. Additionally, it does not disclose the async behavior indicated by the async parameter. This contradiction and lack of detail result in poor transparency.

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?

The description is three sentences with no wasted words: first sentence explains purpose, second lists inputs, third describes outputs. It is front-loaded and every sentence earns its place.

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?

Despite having an output schema, the description fails to mention the async behavior, which is crucial for proper usage. It also contradicts annotations by implying mutation (deletion) despite readOnlyHint. This incompleteness undermines its usefulness.

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%, and the description summarizes inputs (user identifiers, request type, scope filters) but adds no new detail beyond what the schema already provides. It does not explain the async or urgency parameters. Baseline of 3 is appropriate.

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 automates LGPD DSARs for legal teams, specifying Brazil-specific data retention, erasure, and access workflows. It uses a specific verb 'Automates' and identifies the resource, distinguishing it from other privacy tools in the sibling list.

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 implies it is for Brazil-specific LGPD workflows, but does not explicitly state when to use this tool over alternatives or when not to use it. It lacks guidance on exclusions or comparison with other DSAR tools.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All gapup-mcp tools Inspect

Try in Browser

RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

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

Need Help?