webpage_to_markdown
Convert a public webpage or URL into clean Markdown for AI agents, with core retrieval metadata.
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | ||
| max_chars | No | ||
| force_browser | No |
SmartFetch
Schema Changelog
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
- First observed
TDQS
C2.4/5.0
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 converts public webpages to Markdown, but does not disclose whether it uses a headless browser (despite the force_browser parameter), any authentication requirements, rate limits, or what 'core retrieval metadata' actually includes. The behavior is underexplained, leaving the agent uncertain about side effects or prerequisites.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence that states the core purpose without fluff. It is efficiently worded and the key action and resource are front-loaded. However, it is so brief that it omits critical details, but that is a completeness issue rather than a conciseness one.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 3 parameters, no annotations, no output schema, and no parameter descriptions, the description is severely incomplete. It does not explain the max_chars and force_browser parameters, nor what 'core retrieval metadata' means or what the output structure is. An agent cannot invoke this tool correctly without additional knowledge, so this fails the completeness bar.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 0% description coverage and the description does not mention any of the three parameters. The agent cannot learn what max_chars controls (character limit), what force_browser does (browser rendering), or any constraints beyond the schema titles. The description completely fails to add meaning to the schema, which is unacceptable given the low coverage.
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 verb 'Convert' and the resource 'public webpage or URL', with an explicit output 'clean Markdown'. It is specific enough to tell the agent what the tool does, but it does not differentiate from sibling tools like extract_webpage_text or fetch_webpage, which might also convert web content. The mention of 'core retrieval metadata' hints at a distinguishing feature but does not elaborate.
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 the siblings. There is no mention of scenarios where this is preferred over extract_webpage_text, fetch_webpage, or render_webpage. The agent is left to infer from the tool name alone, which is insufficient for correct selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Try in Browser
Glama MCP Gateway
Add one secure layer between your agents and this server.
TDQS
C2.6/5.0
Disambiguation1/5
All four tools describe essentially the same operation: fetching or extracting a webpage and returning clean text/Markdown. fetch_webpage explicitly includes browser rendering and Markdown output, so it overlaps with every other tool and leaves no clear basis for selecting among them.
Naming Consistency3/5
Most names follow a verb-first snake_case pattern (fetch_webpage, render_webpage, extract_webpage_text), but webpage_to_markdown breaks the pattern by using a noun_to_noun form. The naming is readable but not fully consistent.
Tool Count2/5
Four tools is not inherently excessive, but the set is highly redundant for a narrow fetch/extract purpose; one comprehensive tool or at most a two-tool split would be more appropriate. The current count inflates the surface without adding distinct capabilities.
Completeness3/5
The core job of fetching and converting public webpages to text/Markdown is covered, including browser rendering for JavaScript-heavy pages. However, the surface is so overlapping that it lacks meaningful capability stages or distinct output modes beyond the bundled text/Markdown/metadata payload.