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Glama
oschwald

MaxMindDB MCP Server

Verify a database

verify_database
Read-onlyIdempotent

Check a loaded MMDB for structural corruption after importing a database or encountering decode errors; returns valid=true or a verification error.

Instructions

Check a loaded MMDB for structural corruption, such as after importing a database or encountering decode errors. Returns valid=true on success or a verification error. Use inspect_database for metadata and field samples. Only one verification runs at a time. Cancellation can stop a queued request, but verification runs to completion once started.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
databaseYesExact filename of a loaded database from list_databases.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
validYes
databaseYes
completed_after_cancellationYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv0.3.1
    • addedInput schema / properties / database / description
      Added value: +"Exact filename of a loaded database from list_databases."
  2. First observedv0.1.0

TDQS

A4.7/5.0
Behavior5/5

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

Annotations already cover safety (readOnly, idempotent, non-destructive), and the description adds non-obvious operational traits: only one verification runs at a time, cancellation can only stop a queued request, and a started verification runs to completion. It also states the success signal (valid=true) versus a verification error, which is behavior rather than schema restatement.

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?

Four tight sentences, front-loaded with purpose, then error context, then the sibling routing, then concurrency/cancellation limits. Each sentence carries distinct information an agent needs before calling.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

An output schema exists, so return values need not be explained, and the description nonetheless signals success/failure shape. Combined with the usage trigger, sibling routing, and concurrency/cancellation semantics, nothing needed to invoke this correctly is missing.

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

Parameters3/5

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

There is a single parameter and schema coverage is 100%, so the schema already documents 'database' fully, including that it must be an exact filename from list_databases. The description adds no syntax, format, or default information beyond the schema, so the baseline of 3 applies.

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

Purpose5/5

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

States a specific verb and resource — checking a loaded MMDB for structural corruption — and immediately distinguishes itself from the sibling 'inspect_database for metadata and field samples'. An agent can tell verify_database apart from inspect_database without opening either schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Gives explicit triggers ('after importing a database or encountering decode errors') and names the alternative tool plus the condition that selects it (metadata/field samples → inspect_database). Nothing about when to choose this tool is left to inference.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.