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Postgres MCP Pro

Postgres MCP Pro

by sparta2025
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

analyze_db_health

Identify database issues with a full health overview of PostgreSQL. Run all health checks to assess status, spot anomalies, and prevent performance degradation.

Instructions

Database health overview.

Args:
    health_type: Принимается для совместимости со старой схемой
        инструмента, но пока не используется — отчёт всегда
        включает все проверки (default: "all").
    database_url: Database URL (optional, uses DATABASE_URL from .env if omitted).

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": "analyze_db_health"
  }
}

Input Schema

NameRequiredDescriptionDefault
health_typeNoall
database_urlNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.4.2

TDQS

B3.3/5.0
Behavior3/5

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

With no annotations provided, the description carries the behavioral disclosure burden. It does disclose an important behavior: health_type is currently ignored and the report always includes all checks. However, it does not state whether the operation is read-only, what the report contains, or any side effects, leaving meaningful gaps.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is short and front-loaded, with the core statement first and parameter details in a compact Args block. Every sentence contributes useful information, and there is no redundant filler.

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 tool with only two optional parameters, the input documentation is nearly complete. However, there is no output schema and no description of what the returned health report contains, which checks are run, or how the result is structured. The description is adequate but leaves the tool's behavior and return value under-specified.

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

Parameters5/5

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

Schema coverage is 0%, so the description must fully document the parameters, and it does. health_type is explicitly marked as unused and defaulting to 'all', while database_url is documented as optional with a .env fallback. Both parameters receive semantic meaning beyond the bare schema titles and defaults.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description identifies the resource as 'database health' but uses the noun phrase 'overview' rather than a specific verb like 'run' or 'analyze'. It does not differentiate itself from sibling tools such as get_database_info or analyze_index_performance, leaving the agent to infer what makes this tool distinct.

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?

The description explains that health_type is accepted for compatibility and that the report always includes all checks, but it gives no guidance on when to choose this tool over alternatives like analyze_index_performance or get_table_sizes. No exclusions or alternative-selection criteria are provided.

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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