Fetch a URL, return clean HTML (structure kept, scripts/styles stripped). Free. Site migration.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | Page URL. | |
| headers | No | Headers to forward (Authorization, Cookie…). | |
| maxChars | No | Default 16000, max 64000. |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / properties / headers / descriptionAdded value: +"Headers to forward (Authorization, Cookie…)."Input schema / properties / maxChars / descriptionAdded value: +"Default 16000, max 64000."Input schema / properties / url / descriptionAdded value: +"Page URL."Input schema / properties / headersAdded value: +{
+ "type": "object"
+}Input schema / properties / maxChars / descriptionRemoved value: -"Max characters to return (default 16000, max 64000)."Input schema / properties / url / descriptionRemoved value: -"The URL to fetch (http:// or https://)."Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The readOnlyHint annotation already marks this as safe, so the extra context about 'scripts/styles stripped' and 'structure kept' adds meaningful behavioral transparency. It clarifies the transformation applied, though it omits error/redirect behavior or rate limits, which are not critical given the annotation.
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 brief and front-loaded with the core action. 'Free.' and 'Site migration.' are terse but each convey a distinct fact. No redundant filler, though two one-word sentences are abrupt.
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 read-only fetch tool, this description covers purpose, output behavior, cost, and use case. The schema covers all parameters. It could mention truncation behavior for maxChars, but that is a minor gap for a tool of this simplicity.
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 coverage is 100% with clear descriptions for url, headers, and maxChars. The description adds no parameter-specific meaning beyond the schema, so the baseline of 3 applies.
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?
Description clearly states the action ('Fetch a URL') and the specific output ('clean HTML, structure kept, scripts/styles stripped'), which differentiates it from siblings like html_to_markdown or fetch_extract. The behavior is specific and 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 clause 'Site migration' hints at a use case but does not explicitly state when to prefer this tool over alternatives or provide exclusions. There is no mention of sibling tools or conditions where another tool would be more appropriate.
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.
Several tools overlap in fetching and processing web content (fetch_extract, fetch_html, fetch_metadata, html_to_markdown), which could confuse an agent. However, descriptions clarify output types, so most tools are distinguishable.
Names follow mixed conventions: verb_noun (fetch_html, remove_background), noun_verb (csv_query, rss_parse), and noun_noun (tool_catalog, screenshot_url). Each name is descriptive, but the lack of a consistent pattern makes it harder to guess tool names.
With 17 tools, the count is slightly above the ideal 3-15 range but still manageable. The inclusion of 5 meta-tools (pricing, tool_catalog, task_recipes, memory_snippet, use_tool) inflates the count but serves a discovery purpose.
The toolkit covers a broad range of web and data tasks (fetch, parse, query, convert, image, SEO). Minor gaps exist (e.g., no OCR, no image editing), but use_tool can dynamically access additional tools, mitigating incompleteness.