MCP LLMS.txt Explorer
The MCP LLMS.txt Explorer server helps discover and analyze websites implementing the llms.txt standard.
Check websites: Verify if a website has llms.txt or llms-full.txt files by providing the URL
List compliant websites: Get structured data about websites with LLMS files, with filtering options
Parse and validate: Analyze llms.txt files for standard compliance
Integration: Works with Claude Desktop for seamless usage
Debugging support: Includes MCP Inspector for troubleshooting
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@MCP LLMS.txt Explorercheck if openai.com has an llms.txt file"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
MCP LLMS.txt Explorer
A Model Context Protocol server for exploring websites with llms.txt files. This server helps you discover and analyze websites that implement the llms.txt standard.
Features
Resources
Check websites for llms.txt and llms-full.txt files
Parse and validate llms.txt file contents
Access structured data about compliant websites
Tools
check_website- Check if a website has llms.txt filesTakes domain URL as input
Returns file locations and validation status
list_websites- List known websites with llms.txt filesReturns structured data about compliant websites
Supports filtering by file type (llms.txt/llms-full.txt)
Related MCP server: MCP LLMS-TXT Documentation Server
Development
Install dependencies:
pnpm installBuild the server:
pnpm run buildFor development with auto-rebuild:
pnpm run watchInstallation
Installing via Smithery
To install mcp-llms-txt-explorer for Claude Desktop automatically via Smithery:
npx -y @smithery/cli install @thedaviddias/mcp-llms-txt-explorer --client claudeInstalling Manually
To use this server:
# 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 buildConfiguration with Claude Desktop
To use with Claude Desktop, add the server config:
On MacOS: ~/Library/Application Support/Claude/claude_desktop_config.json
On Windows: %APPDATA%/Claude/claude_desktop_config.json
{
"mcpServers": {
"llms-txt-explorer": {
"command": "node",
"args": ["/path/to/llms-txt-explorer/build/index.js"]
}
}
}For npx usage, you can use:
{
"mcpServers": {
"llms-txt-explorer": {
"command": "npx",
"args": ["-y", "@thedaviddias/mcp-llms-txt-explorer"]
}
}
}Debugging
Since MCP servers communicate over stdio, debugging can be challenging. We recommend using the MCP Inspector, which is available as a package script:
pnpm run inspectorThe Inspector will provide a URL to access debugging tools in your browser.
License
This project is licensed under the MIT License—see the LICENSE file for details.
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. Dates show when Glama detected each change.
2 tool updates
- First observed
check_website - First observed
list_websites
TDQS
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
Resources
Unclaimed servers have limited discoverability.
Looking for Admin?
If you are the server author, to access and configure the admin panel.
Related MCP Connectors
Read-only search and discovery for the international llms.txt directory maintained by llmsmap.me.
Checks llms.txt, AI crawler access in robots.txt, and sitemap - with a 0-100 AI readiness score.
Generate 18 AI readiness files (llms.txt, ai.txt, RAG indexes, schema) for any website.
Agent-readiness scanner (0-5 score), robots.txt + llms.txt generators, managed agent enablement.
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