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GeiserX

duplicacy-mcp

by GeiserX

Storage usage

get_storage_usage
Read-onlyIdempotent

Retrieve byte size, chunk count, and retained revision counts per storage target, machine, or snapshot ID to monitor Duplicacy backup usage and capacity.

Instructions

Size in bytes and chunk count of each storage, and how many revisions each snapshot keeps, as the exporter's storage poller last saw them. Empty, with a note, when the poller is off.

Input Schema

NameRequiredDescriptionDefault
machineNoOnly this machine, exactly as list_snapshots returns it in machines, for example "nas". Omit for all.
snapshot_idNoDuplicacy snapshot ID, exactly as list_snapshots returns it, for example "photos".
storage_targetNoOnly this storage target, exactly as list_snapshots returns it in storage_targets, for example "b2". Omit for all.

Output Schema

NameRequiredDescriptionDefault
noteNo
storagesYes
snapshotsYes
poller_errors_totalYesPoller errors since the exporter started
poller_last_successNoTime of the poller's last fully successful cycle, RFC 3339 in UTC

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.2.1

TDQS

A3.6/5.0
Behavior4/5

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

Annotations already declare this a safe, idempotent read, so the bar is lower, and the description still adds real value: the numbers are a stale poller snapshot rather than live data, and an empty result with an explanatory note is returned when the poller is disabled. That is exactly the kind of caveat an agent needs before reporting metrics to a user.

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?

Two tight sentences with no filler; the most decision-relevant fact (staleness) and the failure mode (poller off) are both front-loaded. The opening sentence is a grammatical fragment that takes a second read, which keeps it from a 5.

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?

With a full output schema and complete in-schema parameter docs, the description only needs to supply behavioral caveats — and it does: data freshness and the empty-result condition. Nothing an agent needs to call and interpret 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?

Schema coverage is 100% and each of the three filters is documented in-schema with examples and an 'omit for all' default. The description adds no additional parameter meaning, so the baseline 3 applies.

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 names the resource precisely — per-storage size in bytes and chunk count, plus per-snapshot revision retention — which is distinct from the status/history siblings. It omits an explicit verb (it's a noun-phrase fragment), but the returned data is unambiguous.

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 statement of when to reach for this tool versus get_backup_overview, get_backup_status, or list_snapshots, and no mention that the three filters can scope the result. The only contextual note is a data-availability caveat, not usage guidance.

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