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schema-guard-mcp

schema-guard-mcp

by idk-arsh
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

search_columns

Find columns by name or table name containing a term to locate the right schema fields before writing or validating SQL.

Instructions

Columns whose name (or table name) contains term, e.g. "revenue", "email", "created".

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": {
      "term": "<term>"
    },
    "name": "search_columns"
  }
}

Input Schema

NameRequiredDescriptionDefault
termYes

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.1/5.0
Behavior2/5

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

No annotations exist, so the description carries the full behavioral burden. It discloses substring matching over column and table names, but omits case sensitivity, result limits/pagination, and any read-only/no-side-effect confirmation beyond what the tool name implies.

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?

Single, tightly worded sentence that front-loads the matching scope and examples. It is a fragment rather than a full sentence, but no words are wasted.

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 simple one-parameter search tool with an output schema, the description identifies what is searched but offers no guidance on choosing it over list_tables/describe_table and no behavioral limits. It is minimally adequate but incomplete for an agent deciding among siblings.

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 description coverage is 0% and the only parameter, term, is barely named. The description compensates by defining term as a substring over column name or table name and providing examples, which gives usable semantic meaning beyond the schema type.

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 the resource (columns) and the matching criterion (name or table name contains term) with examples, which is more specific than a bare name. It does not explicitly route against siblings like list_tables or describe_table, but the resource is unambiguous.

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 explicit when-to-use instructions, no alternatives named, no exclusions. Usage is only implied by the description of what is searched; an agent is left to infer when this beats list_tables or describe_table.

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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