Map
mapEnumerate a site's URLs from its sitemap and links, without scraping them.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | The seed URL to map. | |
| limit | No | Max URLs to return. |
mapEnumerate a site's URLs from its sitemap and links, without scraping them.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | The seed URL to map. | |
| limit | No | Max URLs to return. |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, openWorldHint=true, and destructiveHint=false, covering the safety profile. The description adds a meaningful behavioral detail: the tool uses sitemaps and links to discover URLs, and it does not scrape content. This clarifies the method and scope, going beyond what annotations state.
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, tightly packed sentence that delivers the core purpose and a key constraint ('without scraping them') up front. There is no filler or redundancy; every word earns its place.
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 enumeration tool with two parameters and no output schema, the description is adequately complete. It specifies the input (URL), the output concept (URLs), and the discovery method. The only minor gap is that it does not describe the exact output format (e.g., list vs. array), but this is not critical for calling the tool correctly.
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% (both 'url' and 'limit' have descriptions). The tool description repeats some schema info ('from its sitemap and links') but adds no syntax, format, or edge-case details beyond what the schema already provides. Baseline 3 is appropriate given full 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 uses a specific verb ('Enumerate') with a clear resource ('a site's URLs') and method ('from its sitemap and links'). It explicitly distinguishes itself from scraping ('without scraping them'), which differentiates it from the sibling 'scrape' tool. This is a precise and unambiguous statement of the tool's function.
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 phrase 'without scraping them' implies the tool is for URL enumeration rather than content extraction, but it does not explicitly name alternatives or state when to prefer this tool over siblings like 'scrape' or 'extract'. The guidance is implied rather than direct, leaving some inference to the agent.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Most tools target distinct output types like search results, screenshots, images, or styleguides, but scrape and extract overlap significantly in pulling structured data from URLs. Brand and logo also intentionally overlap, with logo being a cheaper subset, though the descriptions do help clarify when to use each.
All tool names are short and lowercase, but they mix imperative verbs like extract, map, scrape, and search with noun-style names like brand, images, logo, and styleguide. There is no consistent verb-noun pattern, though the names remain readable and memorable.
Nine tools is a reasonable size for a web data-fetching server, and each tool covers a plausible retrieval mode. The set is not perfectly lean due to some functional overlap, but nothing feels excessive or redundant enough to hurt usability.
The toolset covers discovery via search and map, content extraction via scrape and extract, and visual/asset needs via screenshot, images, brand, logo, and styleguide. Minor gaps like PDF extraction or raw HTML retrieval exist, but agents can usually work around them.