MCP Webscan Server
The MCP Webscan Server is a tool for scanning and analyzing web content with the following capabilities:
Fetch web pages: Retrieve page content and convert it to Markdown format, with optional CSS selector targeting.
Extract and analyze hyperlinks: Organize links with URLs, anchor text, and contextual details, distinguishing between internal and external links.
Crawl websites: Recursively discover all URLs on a site up to a specified depth.
Check for broken links: Identify and report non-functional links on a given page.
Find links matching patterns: Use regex to locate URLs that match particular patterns.
Generate XML sitemaps: Create sitemaps by crawling a website, useful for SEO and site structure overview.
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 Webscan Serverfetch the content from https://example.com and convert it to markdown"
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 Webscan Server
A Model Context Protocol (MCP) server for web content scanning and analysis. This server provides tools for fetching, analyzing, and extracting information from web pages.
Features
Page Fetching: Convert web pages to Markdown for easy analysis
Link Extraction: Extract and analyze links from web pages
Site Crawling: Recursively crawl websites to discover content
Link Checking: Identify broken links on web pages
Pattern Matching: Find URLs matching specific patterns
Sitemap Generation: Generate XML sitemaps for websites
Related MCP server: Open Crawler MCP Server
Installation
Installing via Smithery
To install Webscan for Claude Desktop automatically via Smithery:
npx -y @smithery/cli install mcp-server-webscan --client claudeManual Installation
# Clone the repository
git clone <repository-url>
cd mcp-server-webscan
# Install dependencies
npm install
# Build the project
npm run buildUsage
Starting the Server
npm startThe server runs on stdio transport, making it compatible with MCP clients like Claude Desktop.
Available Tools
fetch-pageFetches a web page and converts it to Markdown.
Parameters:
url(required): URL of the page to fetch.selector(optional): CSS selector to target specific content.
extract-linksExtracts all links from a web page with their text.
Parameters:
url(required): URL of the page to analyze.baseUrl(optional): Base URL to filter links.limit(optional, default: 100): Maximum number of links to return.
crawl-siteRecursively crawls a website up to a specified depth.
Parameters:
url(required): Starting URL to crawl.maxDepth(optional, default: 2): Maximum crawl depth (0-5).
check-linksChecks for broken links on a page.
Parameters:
url(required): URL to check links for.
find-patternsFinds URLs matching a specific pattern.
Parameters:
url(required): URL to search in.pattern(required): JavaScript-compatible regex pattern to match URLs against.
generate-site-mapGenerates a simple XML sitemap by crawling.
Parameters:
url(required): Root URL for sitemap crawl.maxDepth(optional, default: 2): Maximum crawl depth for discovering URLs (0-5).limit(optional, default: 1000): Maximum number of URLs to include in the sitemap.
Example Usage with Claude Desktop
Configure the server in your Claude Desktop settings:
{
"mcpServers": {
"webscan": {
"command": "node",
"args": ["path/to/mcp-server-webscan/build/index.js"], // Corrected path
"env": {
"NODE_ENV": "development",
"LOG_LEVEL": "info" // Example: Set log level via env var
}
}
}
}Use the tools in your conversations:
Could you fetch the content from https://example.com and convert it to Markdown?Development
Prerequisites
Node.js >= 18
npm
Project Structure (Post-Refactor)
mcp-server-webscan/
├── src/
│ ├── config/
│ │ └── ConfigurationManager.ts
│ ├── services/
│ │ ├── CheckLinksService.ts
│ │ ├── CrawlSiteService.ts
│ │ ├── ExtractLinksService.ts
│ │ ├── FetchPageService.ts
│ │ ├── FindPatternsService.ts
│ │ ├── GenerateSitemapService.ts
│ │ └── index.ts
│ ├── tools/
│ │ ├── checkLinksTool.ts
│ │ ├── checkLinksToolParams.ts
│ │ ├── crawlSiteTool.ts
│ │ ├── crawlSiteToolParams.ts
│ │ ├── extractLinksTool.ts
│ │ ├── extractLinksToolParams.ts
│ │ ├── fetchPageTool.ts
│ │ ├── fetchPageToolParams.ts
│ │ ├── findPatterns.ts
│ │ ├── findPatternsToolParams.ts
│ │ ├── generateSitemapTool.ts
│ │ ├── generateSitemapToolParams.ts
│ │ └── index.ts
│ ├── types/
│ │ ├── checkLinksTypes.ts
│ │ ├── crawlSiteTypes.ts
│ │ ├── extractLinksTypes.ts
│ │ ├── fetchPageTypes.ts
│ │ ├── findPatternsTypes.ts
│ │ ├── generateSitemapTypes.ts
│ │ └── index.ts
│ ├── utils/
│ │ ├── errors.ts
│ │ ├── index.ts
│ │ ├── logger.ts
│ │ ├── markdownConverter.ts
│ │ └── webUtils.ts
│ ├── initialize.ts
│ └── index.ts # Main server entry point
├── build/ # Compiled JavaScript (Corrected)
├── node_modules/
├── .clinerules
├── .gitignore
├── Dockerfile
├── LICENSE
├── mcp-consistant-servers-guide.md
├── package.json
├── package-lock.json
├── README.md
├── RFC-2025-001-Refactor.md
├── smithery.yaml
└── tsconfig.jsonBuilding
npm run buildDevelopment Mode
npm run devRunning evals
The evals package loads an mcp client that then runs the index.ts file, so there is no need to rebuild between tests. You can load environment variables by prefixing the npx command. Full documentation can be found here.
OPENAI_API_KEY=your-key npx mcp-eval src/evals/evals.ts src/tools/extractLinksTool.tsError Handling
The server implements comprehensive error handling:
Invalid parameters
Network errors
Content parsing errors
URL validation
All errors are properly formatted according to the MCP specification.
Contributing
Fork the repository
Create your feature branch (
git checkout -b feature/amazing-feature)Commit your changes (
git commit -m 'Add some amazing feature')Push to the branch (
git push origin feature/amazing-feature)Open a Pull Request
License
MIT License - see the LICENSE file for details
Available Tools
6 toolscheck-linksA
Fetches a given URL, extracts all anchor ('a') links, and checks each linked URL for validity (reachability via HEAD request). Returns a list of checked links with their status ('valid', 'broken', or 'invalid_url' if the href attribute couldn't be resolved to a full URL).
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | The fully qualified URL of the web page to check for broken links. Must be a valid HTTP or HTTPS URL. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden and does well by disclosing key behaviors: it fetches a URL, extracts anchor links, performs HEAD requests for validation, and categorizes results into three status types. It doesn't mention rate limits, timeouts, or authentication needs, but covers the core operational behavior adequately.
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 perfectly concise and front-loaded: a single sentence that efficiently explains the entire workflow from input to output. Every word earns its place with no redundancy or wasted text.
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 single-parameter tool with no annotations and no output schema, the description provides excellent context about what the tool does and what it returns. It could be more complete by mentioning potential limitations (e.g., JavaScript-rendered links, redirect handling) or output format details, but covers the essentials well.
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 fully documents the single 'url' parameter. The description adds no additional parameter semantics beyond what's in the schema (e.g., it doesn't specify URL format requirements or examples). 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 with specific verbs ('fetches', 'extracts', 'checks') and resources ('URL', 'anchor links'), distinguishing it from siblings like 'extract-links' (which likely only extracts) or 'fetch-page' (which likely only fetches). It explicitly mentions what makes this tool unique: checking link validity with status categorization.
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 implies usage context by specifying it checks 'broken links' and handles 'invalid_url' cases, but doesn't explicitly state when to use this tool versus alternatives like 'crawl-site' or 'extract-links'. It provides clear functional context but lacks explicit comparative guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
crawl-siteA
Recursively crawls a website starting from a given URL up to a specified maximum depth. It follows links within the same origin and returns a list of all unique URLs found during the crawl.
| Name | Required | Description | Default |
|---|---|---|---|
| maxDepth | No | The maximum depth to crawl relative to the starting URL. 0 means only the starting URL is fetched. Max allowed depth is 5 to prevent excessive crawling. Defaults to 2. | |
| url | Yes | The starting URL for the crawl. Must be a valid HTTP or HTTPS URL. |
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. It discloses key behaviors: recursion, same-origin link following, and returning unique URLs. However, it lacks details on rate limits, timeouts, authentication needs, or error handling, which are important for a crawling operation. The description does not contradict any annotations.
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 two sentences, front-loaded with the core purpose and followed by behavioral details. Every sentence earns its place by explaining the crawling process and output without redundancy or fluff, making it highly efficient and easy to parse.
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 tool's complexity (crawling with recursion and depth limits), no annotations, and no output schema, the description is adequate but incomplete. It covers the basic operation and output format (list of unique URLs), but lacks information on pagination, response structure, or potential side effects, which could hinder an agent's ability to use it effectively in varied contexts.
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 fully documents parameters. The description adds minimal value beyond the schema by mentioning 'starting URL' and 'maximum depth' in context, but does not provide additional semantics like examples or edge cases. With high schema coverage, the baseline is 3, but the description slightly enhances understanding, warranting a 4.
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 specific action ('recursively crawls'), resource ('a website'), and scope ('starting from a given URL up to a specified maximum depth'). It distinguishes from siblings by specifying it follows links within the same origin and returns unique URLs, unlike tools like 'fetch-page' (single page) or 'extract-links' (link extraction without crawling).
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 implies usage for discovering all URLs on a site via crawling, but does not explicitly state when to use this tool versus alternatives like 'check-links' (likely for link validation) or 'generate-site-map' (for structured sitemaps). No exclusions or prerequisites are mentioned, leaving some ambiguity about optimal use cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
extract-linksA
Extract and analyze all hyperlinks from a web page, organizing them into a structured format with URLs, anchor text, and contextual information. Performance-optimized with stream processing and worker threads for efficient handling of large pages. Works with either a direct URL or raw HTML content. Handles relative and absolute URLs properly by supporting an optional base URL parameter. Results can be limited to prevent overwhelming output for link-dense pages. Returns a comprehensive link inventory that includes destination URLs, link text, titles (if available), and whether links are internal or external to the source domain. Useful for site mapping, content analysis, broken link checking, SEO analysis, and as a preparatory step for targeted crawling operations.
| Name | Required | Description | Default |
|---|---|---|---|
| baseUrl | No | Optional base URL to resolve relative links against. If provided, only links starting with this base URL will be returned. Useful for focusing on internal links. | |
| limit | No | Maximum number of links to return. Defaults to 100. Max allowed is 5000. | |
| url | Yes | The fully qualified URL of the web page from which to extract links. Must be a valid HTTP or HTTPS URL. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes key traits: performance optimization ('stream processing and worker threads for efficient handling of large pages'), input flexibility ('works with either a direct URL or raw HTML content'), URL handling ('handles relative and absolute URLs properly'), output control ('results can be limited to prevent overwhelming output'), and return content ('returns a comprehensive link inventory'). However, it does not mention error handling, rate limits, or authentication needs, leaving some gaps.
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 appropriately sized and front-loaded, starting with the core purpose and key features. Most sentences add value, such as performance optimization and use cases, though some details (e.g., 'stream processing and worker threads') could be slightly condensed. Overall, it is efficient with minimal waste.
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 tool's moderate complexity (3 parameters, no output schema, no annotations), the description is largely complete. It covers purpose, behavioral traits, and usage context effectively. However, without an output schema, it should ideally describe the return format more explicitly (e.g., structure of the 'comprehensive link inventory'), though it does mention included elements like URLs, anchor text, and internal/external classification.
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%, providing detailed documentation for all parameters (url, baseUrl, limit). The description adds marginal value by mentioning the optional base URL parameter for focusing on internal links and limiting results for link-dense pages, but does not provide additional syntax, format, or usage details beyond what the schema already covers. This meets the baseline of 3 when schema coverage is high.
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 specific action ('extract and analyze all hyperlinks from a web page') and resource ('web page'), distinguishing it from siblings like 'check-links' (which likely verifies link status) or 'crawl-site' (which follows links recursively). It explicitly mentions organizing links into a structured format with URLs, anchor text, and contextual information, making the purpose distinct and well-defined.
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 clear context for when to use this tool ('useful for site mapping, content analysis, broken link checking, SEO analysis, and as a preparatory step for targeted crawling operations'), but does not explicitly state when not to use it or name specific alternatives among siblings. It implies usage for extracting links from a single page rather than crawling multiple pages, but lacks direct comparisons to tools like 'crawl-site' or 'generate-site-map'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
fetch-pageA
Fetches the HTML content of a given URL. Optionally, it can select a specific part of the HTML using a CSS selector and convert only that part (or the whole body if no selector is provided) to Markdown format. Returns the resulting Markdown text.
| Name | Required | Description | Default |
|---|---|---|---|
| selector | No | Optional CSS selector (e.g., '#main-content', '.article-body'). If provided, only the HTML content within the first matching element will be converted to Markdown. If omitted or if the selector doesn't match, the content of the 'body' tag will be used. | |
| url | Yes | The fully qualified URL of the web page to fetch. Must be a valid HTTP or HTTPS URL. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It describes the core behavior (fetching HTML, CSS selection, Markdown conversion) and fallback behavior (uses body tag if selector doesn't match). However, it doesn't mention error handling, rate limits, authentication needs, or performance characteristics that would be important for a web fetching tool.
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 efficiently structured in three sentences: purpose statement, optional functionality, and return value. Every sentence earns its place by adding distinct information without redundancy. It's appropriately sized for a tool with two parameters and clear functionality.
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 tool with no annotations and no output schema, the description provides good coverage of what the tool does, how parameters interact, and what it returns. It could be more complete by mentioning potential limitations (e.g., JavaScript-rendered content, timeouts) or authentication requirements, but covers the essential functionality well given the context.
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 schema has 100% description coverage, providing excellent parameter documentation. The description adds value by explaining the relationship between parameters (selector is optional, affects what gets converted) and the overall workflow (fetch → optionally select → convert to Markdown). It provides context beyond individual parameter descriptions.
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 with specific verbs ('fetches', 'select', 'convert') and resources ('HTML content', 'URL', 'Markdown format'). It distinguishes from siblings like 'check-links' or 'extract-links' by focusing on content retrieval and conversion rather than link analysis or crawling.
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 implies usage through its functional explanation (fetch HTML, optionally select with CSS, convert to Markdown), but doesn't explicitly state when to use this tool versus alternatives like 'crawl-site' for multiple pages or 'extract-links' for link extraction. No explicit when-not or alternative guidance is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
find-patternsA
Fetches a web page, extracts all anchor ('a') links, resolves their absolute URLs, and returns a list of links whose URLs match a given JavaScript-compatible regular expression pattern. Includes the URL and anchor text for each match.
| Name | Required | Description | Default |
|---|---|---|---|
| pattern | Yes | A JavaScript-compatible regular expression pattern (without enclosing slashes or flags) used to test against the absolute URLs of the links found on the page. Example: 'product\/\d+' to find product links. | |
| url | Yes | The fully qualified URL of the web page to search for link patterns. Must be a valid HTTP or HTTPS URL. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It describes the tool's behavior well (fetching, extracting, resolving, filtering links) but lacks details on error handling, performance characteristics (e.g., timeouts, rate limits), or authentication needs. It doesn't contradict any annotations.
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 front-loaded with the core functionality in a single, efficient sentence. Every phrase adds value: it specifies the action, the resource (anchor links), the processing (resolving URLs), the filtering mechanism (regex pattern), and the output format (list with URL and anchor text). No wasted words.
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 tool's moderate complexity (web scraping with regex filtering), no annotations, and no output schema, the description is mostly complete. It explains what the tool does and the output format but could benefit from mentioning potential limitations (e.g., handling of JavaScript-rendered content or pagination). It adequately covers the core functionality without being exhaustive.
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 schema description coverage is 100%, providing detailed documentation for both parameters. The description adds minimal value beyond the schema by mentioning the regex is used to 'test against the absolute URLs' and that it returns 'URL and anchor text for each match,' but doesn't explain parameter interactions or edge cases. Baseline 3 is appropriate given the comprehensive schema.
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 specific action ('fetches a web page, extracts all anchor links, resolves their absolute URLs, and returns a list of links') and distinguishes it from siblings by specifying the filtering mechanism ('match a given JavaScript-compatible regular expression pattern'). It goes beyond a simple tautology by detailing the multi-step process.
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 clear context for when to use this tool (finding links matching a regex pattern on a web page) but doesn't explicitly mention when not to use it or name alternatives among the sibling tools. It implies usage for pattern-based link extraction without direct comparison to tools like 'extract-links' or 'fetch-page'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
generate-site-mapA
Crawls a website starting from a given URL up to a specified depth and generates an XML sitemap containing the discovered URLs (up to a specified limit).
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Maximum number of URLs to include in the generated sitemap XML. Defaults to 1000. Max allowed is 5000. | |
| maxDepth | No | The maximum depth to crawl relative to the starting URL to discover pages for the sitemap. 0 means only the starting URL. Max allowed depth is 5. Defaults to 2. | |
| url | Yes | The starting URL for the crawl to generate the sitemap. Must be a valid HTTP or HTTPS URL. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It describes the crawling process and output generation, but lacks details on performance (e.g., rate limits, timeouts), error handling, or authentication needs. It mentions constraints ('up to a specified limit', 'up to a specified depth'), which adds some context, but overall behavioral traits are minimally covered.
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, well-structured sentence that efficiently conveys the core functionality without redundancy. It front-loads key actions ('crawls', 'generates') and includes essential constraints, making every word contribute meaningfully to understanding the tool's purpose.
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 tool's moderate complexity (crawling with depth/limit constraints) and no annotations or output schema, the description is adequate but incomplete. It covers the basic operation and output type, but lacks details on return values (e.g., XML structure, error responses) and behavioral aspects like performance or prerequisites, which are needed for full contextual understanding.
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 fully documents all parameters (url, maxDepth, limit) with details like defaults, ranges, and formats. The description adds no additional parameter semantics beyond what the schema provides, such as explaining interactions between parameters or edge cases, meeting the baseline for high schema coverage.
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 specific action ('crawls a website', 'generates an XML sitemap') and the resource ('discovered URLs'), distinguishing it from siblings like 'check-links' (validation) or 'fetch-page' (single page retrieval). It explicitly mentions the scope ('starting from a given URL up to a specified depth') and output format ('XML sitemap'), making the purpose unambiguous.
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 like 'crawl-site' or 'extract-links'. It does not mention prerequisites, exclusions, or comparative contexts, leaving the agent to infer usage solely from the tool name and description without explicit direction.
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.
6 tool updates
v1.0.0- First observed
check-links - First observed
crawl-site - First observed
extract-links - First observed
fetch-page - First observed
find-patterns - First observed
generate-site-map
TDQS
There is significant overlap between tools, particularly check-links, extract-links, and find-patterns, which all involve extracting and analyzing links from web pages, leading to potential confusion. However, crawl-site and generate-site-map have more distinct purposes for recursive crawling and sitemap generation, respectively, and fetch-page stands out for content retrieval and conversion.
All tool names follow a consistent kebab-case pattern with clear verb-noun structures (e.g., check-links, crawl-site, extract-links). This uniformity makes the tool set predictable and easy to navigate, with no deviations in naming style.
With 6 tools, the count is well-scoped for a web scanning server, covering key operations like link checking, crawling, content fetching, and sitemap generation. Each tool has a clear role, avoiding bloat while providing comprehensive coverage for the domain.
The tool set covers core web scanning tasks such as link extraction, validation, crawling, and sitemap generation, with fetch-page adding content retrieval and conversion. A minor gap exists in lacking tools for security scanning (e.g., vulnerability checks) or performance analysis, but the provided tools support most common workflows effectively.
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