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oracle-db-mcp

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Python
Remote

list_tables

Fetch all tables from an Oracle database with support for name pattern filtering and pagination.

Instructions

Get a list of all tables in the oracle database with optional filtering and pagination

Args:
    pattern (string, optional): Filter tables by name pattern (case-insensitive)
    limit (int, optional): Maximum number of tables to return. Default is 50
    offset (int, optional): Number of tables to skip. Default is 0

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
offsetNo
patternNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.0.1

TDQS

B3.1/5.0
Behavior2/5

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

With no annotations, the description carries the full behavioral burden, but it only covers pagination defaults and pattern case-insensitivity. It says nothing about read-only guarantees, ordering of results, whether system/schema tables are included, permission requirements, or how large result sets behave.

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 purpose is front-loaded in a single clear sentence, followed by a compact Args block. The structure is efficient and easy to scan, with little wasted language.

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 read-only list tool with no output schema, the essentials are present, but the agent still lacks context on what a returned table entry contains, whether results are scoped to a schema/owner, and result ordering. Adequate but with clear gaps.

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%, so the description must compensate, and it does: all three parameters are documented with meaning, optionality, and defaults (pattern is a case-insensitive name filter, limit defaults to 50, offset defaults to 0). Only minor gaps remain, such as any upper bound on limit or the pattern matching syntax.

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 states a specific verb and resource ('Get a list of all tables in the oracle database') plus scope modifiers (filtering/pagination), so the agent knows exactly what the tool returns. It does not, however, distinguish itself from close siblings like list_schemas or list_objects, which also enumerate database entities.

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_objects, list_schemas, or describe_table. Usage is only implied by the tool name and the word 'tables'; no prerequisites, exclusions, or alternative-routing advice is given.

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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