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Grubbomatic

Crawl Readiness MCP Server

Generate robots.txt

generate_robots_txt

Generate a ready-to-save robots.txt for any website, merging existing rules with AI-crawler policies. Choose a preset (allow-all, search-only, recommended, or block-all) to control AI access.

Instructions

Generate a complete, ready-to-save AI-crawler-aware robots.txt for a website. Fetches the existing robots.txt (if any) and returns the finished file in generated.robotsTxt — the existing rules with an AI-crawler policy section merged in — plus the per-bot allow/block breakdown. Presets: 'allow-all' (public businesses), 'search-only' (allow AI search, block training), 'recommended' (allow major AI assistants that cite sources, block training-only bots), 'block-all'. Write generated.robotsTxt to the site's /robots.txt. Requires an API key.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesThe website to generate a robots.txt for.
presetNoThe AI-crawler policy preset to apply.recommended

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.3

TDQS

A4.4/5.0
Behavior4/5

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

Beyond the readOnlyHint=false annotation, the description discloses meaningful side effects: it fetches the existing robots.txt, writes generated.robotsTxt to /robots.txt, and requires an API key. It also describes the return payload (generated file plus per-bot allow/block breakdown), giving the agent a clear picture of behavior.

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 dense but each sentence earns its place: purpose, workflow, presets, side effect, and auth requirement. The important behavioral information is front-loaded and the preset list is structured and 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?

For a two-parameter tool with no output schema, the description covers the return value, the side effect, the presets, and the auth requirement. It could be more complete by limiting when to use it vs. sibling tools, but it is adequate for a competent 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?

Schema coverage is 100%, so the baseline is 3, but the description adds real value by explaining the meaning of each preset ('allow-all', 'search-only', 'recommended', 'block-all') and their intended use cases. It does not add syntax details for url, but the schema already documents that parameter.

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 names a specific deliverable ('AI-crawler-aware robots.txt') and a concrete workflow (fetch, merge, write), which differentiates it from sibling validation/generation tools. The opening sentence states exactly what the tool produces for a website.

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 for when to use the tool: to generate a ready-to-save robots.txt with an AI-crawler policy, and it enumerates preset policies for different site stances. It does not explicitly say 'use validate_robots instead for validation', but this is not necessary for correct selection given the sibling names.

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