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BunkerWeb MCP

BunkerWeb MCP

Official
by bunkerity
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

list_services

Read-only

Lists BunkerWeb services with IDs, methods, draft status, templates, security modes, and dates, optionally excluding drafts; results may be cached for up to five minutes.

Instructions

List services (id, method, is_draft, template, security mode, dates); with_drafts=false hides drafts. Cached up to 5 min. Use get_service for one service's settings, get_global_config for global ones.

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_services"
  }
}

Input Schema

NameRequiredDescriptionDefault
with_draftsNoInclude draft services

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv0.5.0
    • addedInput schema / properties / with_drafts / description
      Added value: +"Include draft services"
  2. First observedv0.1.0

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, so safety is covered; the description adds a genuinely useful behavioral trait not in the annotations — results are cached up to 5 minutes, which tells the agent to expect staleness after a mutation. It does not discuss ordering, pagination, or result size, which is the remaining gap for a list tool.

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?

One dense sentence plus two short routing clauses; the field list and the draft-filter rule come first, and the alternatives come last. No filler wording at all.

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?

For a one-parameter read-only list tool with no output schema, the description covers what is returned, the filter behavior, freshness characteristics, and sibling routing. Nothing an agent needs in order to call it 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 the single parameter is already documented as "Include draft services" with default true. The description's "with_drafts=false hides drafts" only restates the schema in negative framing, adding negligible new meaning. Baseline 3 applies when the schema carries the semantics.

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 opens with a specific verb and resource ("List services") and immediately enumerates the fields returned (id, method, is_draft, template, security mode, dates), so an agent knows exactly what this returns without opening a schema. It also names the sibling tools it is not (get_service, get_global_config), making selection unambiguous.

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?

It explicitly routes the agent: use get_service for a single service's settings and get_global_config for global configuration. The with_drafts=false condition is stated as a concrete usage rule, leaving no inference required.

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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