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pihole-mcp

pihole-mcp

by chris2ao
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

search_domain

Explain why a domain is blocked or allowed in Pi-hole by showing matching domain-list entries, regexes, adlists, and groups. Supports partial substring matching and result limits.

Instructions

Explain why a domain is blocked or allowed: shows matching domain-list entries, regexes, and adlists (gravity), with the groups each applies to.

partial=true also matches substrings. max_results caps results per category.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "domain": "<domain>"
    },
    "name": "search_domain"
  }
}

Input Schema

NameRequiredDescriptionDefault
domainYes
partialNo
max_resultsNo

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.1.0

TDQS

A3.9/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It discloses matching behavior and what kinds of entries (regexes, adlists, groups) are reported, but never states that the operation is read-only, whether it requires auth, or any rate/scope limits. Useful behavioral context, but incomplete for a no-annotation tool.

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?

Front-loads the purpose in the first clause, then adds a compact second sentence covering both optional parameters. No filler, though the parameter notes could be slightly more scannable.

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

Completeness4/5

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 re-explained, and the description already covers the two non-obvious parameters. What remains thin is behavioral/usage context (read-only nature, when to prefer this over list_domains), which keeps it short of full completeness.

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?

Schema description coverage is 0%, so the description must compensate, and it does: it explains that partial=true enables substring matching and that max_results caps results per category. This meaningfully disambiguates the two non-obvious optional parameters beyond their bare names and defaults.

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 diagnostic goal ('Explain why a domain is blocked or allowed') plus the concrete evidence it surfaces (domain-list entries, regexes, adlists/gravity, applicable groups). This clearly separates it from lookup/list siblings such as list_domains, get_blacklist, and get_query_log.

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

Usage Guidelines3/5

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

The diagnostic framing ('explain why...') implies when the tool is useful, but it never names an alternative or states when not to use it versus siblings like list_domains or get_query_log. Usage is inferable rather than explicit.

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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