DataSearcher MCP

by MarkIvor

Overview Schema Source Related Servers Discussions Admin

Python

Hybrid

scan_pii

Scan a database table to identify personally identifiable information and flag sensitive columns for protection.

Instructions

Сканировать таблицу на PII и пометить чувствительные колонки (ТЗ 10).

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": {
      "table_name": "<table_name>"
    },
    "name": "scan_pii"
  }
}

Input Schema

Name	Required	Description	Default
`table_name`	Yes

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.0.0Sep 1, 2026

TDQS

C2.9/5.0

Behavior2/5

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

No annotations are provided, so the description must disclose behavioral traits. 'Пометить чувствительные колонки' implies a mutation or metadata update, but the description does not say whether the marking is reversible, whether it modifies table metadata, or whether any permissions are required.

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 description is a single sentence with the key action and target front-loaded. The trailing '(ТЗ 10)' reference is project-specific noise that does not help an agent invoke the tool.

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?

For a single-parameter tool with an output schema present, this is mostly callable. However, it omits side-effect disclosure and any usage context relative to the large set of sibling data-analysis tools, leaving gaps in when and how it should be used.

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 0% and table_name has no schema help. The description adds the minimal meaning that the parameter is the table to scan for PII, but it does not cover naming format, qualified names, or error behavior. Some compensation occurs, but it is thin.

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?

The description uses a specific verb ('Сканировать') and resource ('таблицу'), and states the goal: detect PII and mark sensitive columns. This distinguishes it from siblings like profile_data or data_quality_report, though it does not explicitly name an alternative.

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?

No guidance is given about when to use this tool versus siblings such as profile_data, data_quality_report, or semantic_search. The description only states the action, leaving the intended use case to be inferred from the tool name and wording.

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