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robotstxt-ai-mcp

robotstxt-ai-mcp

by sharozdawa
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Remote

list_ai_bots

Retrieve a complete list of known AI bots including user-agents, companies, and descriptions to decide which crawlers to block in your robots.txt.

Instructions

List all known AI bots with their user-agents, companies, and descriptions. Useful for deciding which bots to block.

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_ai_bots"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A4.3/5.0
Behavior3/5

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

No annotations are provided, so the description carries the burden. It indicates a read-only listing operation, but does not explicitly state safety, idempotency, or potential side effects. The name and context imply no destructive behavior, but more clarity could be provided.

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 consists of two short sentences: the first clearly states the purpose and result, and the second gives a usage hint. No superfluous words, well-structured.

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 zero parameters, no output schema, and a simple listing task, the description is fully sufficient. It explains what the tool returns (user-agents, companies, descriptions) and its usefulness. No gaps remain for an agent to invoke it correctly.

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 no parameters and the schema description coverage is 100%. The description adds no parameter details because none are needed. The baseline for zero parameters is 4, and the description fulfills that by not requiring additional explanation.

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 clearly states the tool lists all known AI bots with specific fields (user-agents, companies, descriptions), using a specific verb and resource. It distinguishes from sibling tools like analyze_robots or generate_robots, which have different purposes.

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 context for when to use the tool ('Useful for deciding which bots to block'), implying a decision-making scenario. Though it does not explicitly mention alternatives or when-not-to-use, the intended usage is clear given sibling tool names.

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

Deploy Server

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