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PgSafe MCP

PgSafe MCP

by johannschiffer
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

list_tables

Discover and enumerate all public database tables available for inspection and querying. Use it to identify schemas before running read-only SQL against SQLite or PostgreSQL.

Instructions

List all public database tables available for inspection and querying.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "list_tables"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

B3.3/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden. It discloses one useful scope qualifier ('public', excluding non-public schemas) but says nothing about return format, whether this can be slow on large catalogs, permission requirements, or that it is a read-only operation.

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?

A single front-loaded sentence with no padding. The trailing clause 'available for inspection and querying' is slightly loose but does carry usage context, so it is not waste.

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 zero-parameter read tool with no output schema and no annotations, the description covers the what but omits the practical details an agent would want: whether results are names, schema-qualified identifiers, or metadata, and confirmation that no side effects occur.

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?

The tool takes zero parameters, so per the rubric the baseline is 4. Nothing in the description is needed to disambiguate arguments.

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: 'List all public database tables.' An agent immediately knows this is a discovery/enumeration tool. It does not explicitly differentiate itself from siblings like describe_table or safe_query, so it stops short of 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?

The phrase 'available for inspection and querying' hints that this is the entry point before describe_table or safe_query, but the workflow is only implied. No explicit when-to-use, when-not-to-use, or alternative is named.

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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