A
licenseB
qualityF
maintenanceA server that analyzes website performance using Playwright and Lighthouse, allowing LLMs to perform web performance analysis through the Model Context Protocol.
2
5
MIT
MCP LLMS.txt Explorer
by thedaviddias
MCP LLMS.txt 资源管理器
一个用于探索包含 llms.txt 文件的网站的模型上下文协议 (MCP) 服务器。此服务器可帮助您发现和分析实现 llms.txt 标准的网站。
特征
资源
检查网站上是否有 llms.txt 和 llms-full.txt 文件
解析并验证 llms.txt 文件内容
访问合规网站的结构化数据
工具
check_website- 检查网站是否有 llms.txt 文件将域名 URL 作为输入
返回文件位置和验证状态
list_websites- 使用 llms.txt 文件列出已知网站返回有关合规网站的结构化数据
支持按文件类型过滤（llms.txt/llms-full.txt）
Related MCP server: MCP LLMS-TXT Documentation Server
发展
安装依赖项：
pnpm install构建服务器：
pnpm run build对于使用自动重建的开发：
pnpm run watch安装
通过 Smithery 安装
要通过Smithery自动为 Claude Desktop 安装 mcp-llms-txt-explorer：
npx -y @smithery/cli install @thedaviddias/mcp-llms-txt-explorer --client claude手动安装
要使用此服务器：
# 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 build使用 Claude Desktop 进行配置
要与 Claude Desktop 一起使用，请添加服务器配置：
在 MacOS 上： ~/Library/Application Support/Claude/claude_desktop_config.json在 Windows 上： %APPDATA%/Claude/claude_desktop_config.json
{
"mcpServers": {
"llms-txt-explorer": {
"command": "/path/to/llms-txt-explorer/build/index.js"
}
}
}对于 npx 的使用，您可以使用：
{
"mcpServers": {
"llms-txt-explorer": {
"command": "npx",
"args": ["-y", "@thedaviddias/mcp-llms-txt-explorer"]
}
}
}调试
由于 MCP 服务器通过 stdio 进行通信，调试起来可能比较困难。我们推荐使用MCP Inspector ，它以包脚本的形式提供：
pnpm run inspector检查器将提供一个 URL 来访问浏览器中的调试工具。
执照
该项目根据 MIT 许可证获得许可 - 有关详细信息，请参阅 LICENSE 文件。
Available Tools
2 toolscheck_websiteC
Check if a website has llms.txt files
ParametersJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | URL of the website to check |
TDQS
C2.9/5.0
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden 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.
Conciseness5/5
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.
Completeness2/5
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.
Parameters3/5
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.
Purpose4/5
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.
Usage Guidelines2/5
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
ParametersJSON Schema
| 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
B3.1/5.0
Behavior2/5
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.
Conciseness5/5
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.
Completeness3/5
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.
Parameters3/5
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.
Purpose4/5
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.
Usage Guidelines2/5
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
B3.1/5.0
Scored across 2 tools
Disambiguation5/5
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.
Naming Consistency5/5
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.
Tool Count2/5
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.
Completeness2/5
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
ActivityInactive
ResponsivenessUnresponsive
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
- 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