MCP LLMS.txt Explorer
MCP LLMS.txt 탐색기
llms.txt 파일이 있는 웹사이트를 탐색하기 위한 모델 컨텍스트 프로토콜 서버입니다. 이 서버는 llms.txt 표준을 구현하는 웹사이트를 검색하고 분석하는 데 도움을 줍니다.
특징
자원
llms.txt 및 llms-full.txt 파일을 확인하려면 웹사이트를 확인하세요.
llms.txt 파일 내용 구문 분석 및 검증
규정을 준수하는 웹사이트에 대한 구조화된 데이터에 액세스
도구
check_website- 웹사이트에 llms.txt 파일이 있는지 확인합니다.도메인 URL을 입력으로 사용합니다.
파일 위치 및 유효성 검사 상태를 반환합니다.
list_websites- llms.txt 파일을 사용하여 알려진 웹사이트 나열규정을 준수하는 웹사이트에 대한 구조화된 데이터를 반환합니다.
파일 유형(llms.txt/llms-full.txt)별 필터링을 지원합니다.
Related MCP server: MCP LLMS-TXT Documentation Server
개발
종속성 설치:
지엑스피1
서버를 빌드하세요:
pnpm run build자동 재빌드를 사용한 개발의 경우:
pnpm run watch설치
Smithery를 통해 설치
Smithery를 통해 Claude Desktop용 mcp-llms-txt-explorer를 자동으로 설치하려면:
npx -y @smithery/cli install @thedaviddias/mcp-llms-txt-explorer --client claude수동 설치
이 서버를 사용하려면:
# Clone the repository
git clone https://github.com/thedaviddias/mcp-llms-txt-explorer.git
cd mcp-llms-txt-explorer
# Install dependencies
pnpm install
# Build the server
pnpm run buildClaude Desktop을 사용한 구성
Claude Desktop과 함께 사용하려면 서버 구성을 추가하세요.
MacOS의 경우: ~/Library/Application Support/Claude/claude_desktop_config.json Windows의 경우: %APPDATA%/Claude/claude_desktop_config.json
{
"mcpServers": {
"llms-txt-explorer": {
"command": "/path/to/llms-txt-explorer/build/index.js"
}
}
}npx를 사용하려면 다음을 사용할 수 있습니다.
{
"mcpServers": {
"llms-txt-explorer": {
"command": "npx",
"args": ["-y", "@thedaviddias/mcp-llms-txt-explorer"]
}
}
}디버깅
MCP 서버는 stdio를 통해 통신하므로 디버깅이 어려울 수 있습니다. 패키지 스크립트로 제공되는 MCP Inspector를 사용하는 것이 좋습니다.
pnpm run inspector검사기는 브라우저에서 디버깅 도구에 액세스할 수 있는 URL을 제공합니다.
특허
이 프로젝트는 MIT 라이선스에 따라 라이선스가 부여되었습니다. 자세한 내용은 라이선스 파일을 참조하세요.
Available Tools
2 toolscheck_websiteC
Check if a website has llms.txt files
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | URL of the website to check |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool checks for 'llms.txt files,' implying a read-only operation, but doesn't specify what 'check' entails (e.g., HTTP request details, error handling, or output format). For a tool with no annotations, this is a significant gap in transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence with no wasted words. It's front-loaded with the core purpose and efficiently conveys the tool's function without unnecessary elaboration, making it highly concise and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of annotations and output schema, the description is incomplete. It doesn't explain what the tool returns (e.g., boolean result, file details, or error messages) or any behavioral aspects like rate limits or authentication needs. For a tool with no structured support, the description should provide more context to be fully helpful.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, with the 'url' parameter fully documented. The description doesn't add any semantic details beyond the schema, such as URL format requirements or examples. Given the high schema coverage, the baseline score of 3 is appropriate, as the schema handles the parameter documentation adequately.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Check if a website has llms.txt files.' It specifies the verb ('check') and resource ('website'), making the action explicit. However, it doesn't differentiate from the sibling tool 'list_websites,' which likely serves a different function (listing vs. checking), so it doesn't reach the highest score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention the sibling tool 'list_websites' or any other context for usage, such as prerequisites or scenarios. This leaves the agent without direction on tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_websitesB
List known websites with llms.txt files
| Name | Required | Description | Default |
|---|---|---|---|
| filter_llms_txt | No | Only show websites with llms.txt | |
| filter_llms_full_txt | No | Only show websites with llms-full.txt |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It mentions that the tool lists websites 'with llms.txt files' but doesn't describe what 'known websites' means, whether this is a read-only operation, what format the output takes, or any limitations (like pagination or rate limits). The description is minimal and lacks important behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise - a single sentence that directly states the tool's purpose. There's zero waste or unnecessary elaboration. It's appropriately sized for a simple listing tool with well-documented parameters.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple listing tool with 100% schema coverage but no annotations and no output schema, the description is adequate but has clear gaps. It explains what the tool does but doesn't provide context about what constitutes 'known websites' or what the output format will be. The description meets minimum viability but could be more complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents both parameters (filter_llms_txt and filter_llms_full_txt) with clear descriptions. The description doesn't add any parameter semantics beyond what's in the schema - it doesn't explain how these filters work together or their default behavior. Baseline 3 is appropriate when schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'List known websites with llms.txt files' specifies both the action (list) and resource (websites with llms.txt files). However, it doesn't explicitly differentiate from the sibling tool 'check_website', which likely serves a different purpose (possibly checking individual websites rather than listing them).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. There's no mention of the sibling tool 'check_website' or any context about when listing websites is appropriate versus checking individual ones. The description simply states what the tool does without usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
2 tool updates
- First observed
check_website - First observed
list_websites
TDQS
Scored across 2 tools
The two tools have clearly distinct purposes: check_website verifies the presence of llms.txt files on a specific website, while list_websites retrieves a list of known websites that already have such files. There is no overlap in functionality, making it easy for an agent to select the appropriate tool based on the task.
Both tools follow a consistent verb_noun pattern (check_website and list_websites), using snake_case and clear action verbs. This uniformity makes the tool set predictable and easy to understand, with no deviations in naming conventions.
With only two tools, the server feels under-scoped for exploring llms.txt files. While the tools cover basic checking and listing, there are likely missing operations such as fetching file contents, updating lists, or analyzing data, which limits the server's utility for comprehensive exploration.
The tool set is severely incomplete for an 'Explorer' server. It lacks essential operations like retrieving the actual llms.txt content, validating file structure, searching within files, or managing the list of websites. This creates significant gaps that will hinder agents from performing meaningful exploration tasks.
Maintenance
Related MCP Connectors
Read-only search and discovery for the international llms.txt directory maintained by llmsmap.me.
Checks whether a website has a usable llms.txt. Score 0–100. Free 3/day/IP, then ¥10.
Free check whether a website is technically open to AI assistants (AI crawlers, llms.txt, JSON-LD).
Checks llms.txt, AI crawler access in robots.txt, and sitemap - with a 0-100 AI readiness score.
Related MCP Servers
- AlicenseBqualityFmaintenanceA server that analyzes website performance using Playwright and Lighthouse, allowing LLMs to perform web performance analysis through the Model Context Protocol.25MIT
- AlicenseNot gradedqualityDmaintenanceAn MCP server that enables users to fetch and audit documentation from user-defined llms.txt index files. It provides tools to list documentation sources and retrieve content from specific URLs with built-in domain access controls for secure context retrieval.MIT
- AlicenseNot gradedqualityBmaintenanceEnables AI agents to extract, validate, and discover documentation from websites using llms.txt and install.md standards.14 npm34-
- AlicenseNot gradedqualityCmaintenanceEnables websites to expose a first-class interface for AI agents by providing read-only MCP tools like search_site and generating llms.txt discovery files.05MIT