LLMS.txt Explorer

The MCP LLMS.txt Explorer fills a niche in the AI tooling ecosystem by enabling assistants to interrogate the web for sites that publish their model‑interaction policies via the emerging llms.txt standard. As more organizations adopt this lightweight, plain‑text format to declare how their language models can be accessed and used, developers need a reliable way to discover, validate, and catalogue these resources. This server provides that capability, acting as a bridge between an AI assistant’s request and the structured information embedded in llms.txt files across the internet.

At its core, the server offers two complementary resources: a website checker and a website list retriever. The checker scans any supplied domain for the presence of llms.txt or its more verbose counterpart, llms‑full.txt, parses the file’s contents, and reports validation status along with the exact locations of the discovered files. The list retriever aggregates known compliant sites, presenting them as structured data that can be filtered by file type. These resources are exposed through the MCP tool interface, allowing an assistant to invoke them with simple prompts such as “Check whether example.com hosts an llms.txt file” or “List all sites that publish llms‑full.txt”.

For developers, this functionality translates into a powerful workflow enhancer. When building AI applications that must respect usage policies—whether for compliance, ethical auditing, or dynamic policy enforcement—the ability to programmatically fetch and verify llms.txt files removes manual overhead. A Claude-powered assistant can automatically surface policy details before invoking a model, ensuring that downstream services operate within the bounds defined by each host. Additionally, the list of compliant sites can serve as a curated dataset for training or benchmarking purposes, offering a ready pool of real‑world policy declarations.

Unique to this MCP server is its focus on the llms.txt standard, a niche yet rapidly growing area of web metadata. By providing both discovery and validation in one place, it eliminates the need for separate scraping or parsing utilities. The server’s design aligns with MCP’s lightweight, stdio‑based communication model, making it easy to integrate into existing AI workflows without additional infrastructure. Whether you’re building a compliance checker, an automated policy‑aware agent, or simply curating a directory of model‑policy documents, the LLMS.txt Explorer gives developers a straightforward, reliable tool to turn unstructured web data into actionable insights.