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backrest-mcp

backrest-mcp

by TadMSTR
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

get_summary

Retrieve a 30-day backup summary for each repository and plan, showing success/warning/failure counts, bytes scanned and added, total snapshots, and the next scheduled backup time.

Instructions

Get the Backrest dashboard summary — 30-day stats per repo and plan.

Returns per-repo and per-plan success/warning/failed backup counts, bytes scanned/added, total snapshots, and the next scheduled backup time.

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": "get_summary"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.3.0

TDQS

A4.5/5.0
Behavior4/5

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

With no annotations provided, the description carries the burden of behavioral disclosure. It clearly states the output (per-repo/per-plan counts, bytes, snapshots, next scheduled time) and the 30-day time range. As a 'Get' operation, it implies read-only behavior, and no side effects are mentioned. This adds useful context without being overly verbose.

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 two sentences: the first front-loads the core purpose, and the second elaborates on the return details. There is no redundant information, and every word adds value.

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?

Given the tool's simplicity, zero parameters, and presence of an output schema (which likely documents the return structure), the description is complete. It details the content of the summary (counts, bytes, snapshots, next scheduled time) and matches the expected dashboard use case. No critical information is missing.

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 has zero parameters, so the description is not required to explain parameter semantics. The baseline for no-parameter tools is 4, and the description appropriately describes what the operation returns without any parameter-related gaps.

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?

The description uses a specific verb 'Get' with a clear resource 'Backrest dashboard summary' and specifies the 30-day stats per repo and plan. This distinguishes it from sibling tools like list_snapshots and list_snapshot_files, which focus on listing individual snapshots rather than aggregated statistics.

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

Usage Guidelines4/5

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

The description provides clear context by indicating this returns a high-level dashboard summary, which implies use for overview and monitoring rather than granular inspection. It does not explicitly mention alternatives or when not to use it, but the context is sufficient for an agent to infer appropriate usage.

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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