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Universal MCP Bridge & Proxy

Universal MCP Bridge & Proxy

by francaroscillidev-gif
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

db_sample_schema

Inspect tables and column schemas in sample.db to understand its structure.

Instructions

Inspect tables and column schemas in database 'sample.db'

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": {
      "kwargs": "<kwargs>"
    },
    "name": "db_sample_schema"
  }
}

Input Schema

NameRequiredDescriptionDefault
kwargsYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.8/5.0
Behavior2/5

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

No annotations are supplied, so the description carries the full behavioral burden and does very little with it. It does not say what 'inspect' returns (table list, DDL, column types), whether it is strictly read-only, how many objects are covered, or whether any cost/limit applies.

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?

One short sentence with no filler and the target database front-loaded. Its brevity is appropriate, though the space saved is not reinvested in the missing parameter or return details.

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?

No annotations, no output schema, and an undocumented required argument mean the definition leaves the agent unable to call the tool or anticipate results. Given the tool's simplicity this is not catastrophic, but the opaque 'kwargs' parameter needed at least one sentence of explanation.

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

Parameters1/5

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

Schema coverage is 0% for the single required parameter, which is an opaque string named 'kwargs'. The description offers no explanation of what that string should contain (table name? filter? serialized arguments?), so an agent cannot reliably construct a valid call.

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 ('Inspect') and resource ('tables and column schemas') scoped to a named database, 'sample.db'. The verb 'inspect' implicitly distinguishes it from the sibling db_sample_query, which reads as execution rather than introspection. No explicit sibling differentiation is stated, keeping it below a 5.

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?

Usage is only implied by the verb: an agent can infer this is the tool for discovering structure before querying with db_sample_query. There is no explicit 'use this when...' statement, no mention of prerequisites, and no exclusion of the query sibling.

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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