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@guardbee/mcp-security-proxy

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db_gateway__query_table

Query database table rows with optional key-value filters while the KVKK/GDPR gateway automatically masks sensitive fields in every result.

Instructions

Query rows from a database table with optional filters. All results pass through the KVKK/GDPR gateway — sensitive fields are automatically masked.

Input Schema

NameRequiredDescriptionDefault
limitNoMax rows to fetch before gateway limit is applied (default 50)
tableYesTable name to query
filterNoKey-value filter pairs, e.g. { status: 'active' }

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv0.1.5
    • changedInput schema / $schema
      Previous value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"
  2. Addedv0.1.1

TDQS

B3.3/5.0
Behavior3/5

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

With no annotations, the description carries the full behavioral burden; it does disclose a genuinely non-obvious trait — that every result is routed through the KVKK/GDPR gateway and sensitive fields are auto-masked. However, it doesn't state that the operation is strictly read-only, what permissions are needed, or how masked values are represented in the returned rows.

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 sentences, front-loaded with the action and scope, then the non-obvious gateway/masking caveat. No filler and nothing redundant.

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?

The tool has no output schema and no annotations, so the description is the only place return behavior could be explained, yet it doesn't describe what a result row looks like or how masking appears. For a query tool with a nested filter object, that leaves a real gap even though the inputs are fully documented.

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%, so table, filter, and limit are all documented with examples and the 200-row cap. The description adds nothing beyond that, so the baseline 3 applies rather than a higher score.

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?

States a specific verb and resource ("Query rows from a database table") with the scope qualifier "optional filters". It is distinguishable from db_gateway__list_tables and db_gateway__describe_table, but it never explicitly names or contrasts with db_gateway__query_audit_log, the closest sibling.

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

Usage Guidelines2/5

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

There is no guidance on when to use this versus list_tables/describe_table (e.g. 'use describe_table first to learn column names') or query_audit_log. The only inferred usage is that a table name is required, which the schema already implies.

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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