Fetch a URL and return content.
Images return as FastMCP Image.
PDFs return as File(format="pdf").
Text/JSON return as a JSON payload with metadata and text.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | HTTP or HTTPS URL to retrieve and normalize. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden and does disclose meaningful behavioral detail: images return as FastMCP Image, PDFs as File, text/JSON as JSON payload. It omits edge cases like redirects or errors, but the included output format details add value beyond the schema.
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 concise and front-loaded, with a bulleted list of return formats. Every sentence adds value and there is no 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 simple single-parameter tool with no output schema, the description adequately covers the main return types. It lacks usage context versus sibling tools and edge-case behavior, but overall it is sufficient for basic invocation.
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 already fully documents the url parameter with 100% coverage. The description adds no additional parameter-specific meaning, so the baseline score of 3 is appropriate.
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 fetches a URL and returns content, with specific output types. It does not explicitly differentiate from sibling tools like convert_url, but the verb+resource combination makes the purpose evident.
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?
No guidance is provided on when to use fetch versus the sibling tools (convert_url, search, etc.). The description explains what happens during a fetch but not the selection criteria or alternatives.
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.
convert and convert_url are clearly differentiated by input source (blob vs URL), while doctype, fetch, and search serve distinct purposes. Minor overlap exists between convert_url and fetch (both fetch remote content), but the conversion vs. plain-fetch distinction is explicit in descriptions.
Tool names use a mix of bare verbs (convert, fetch, search), verb_noun (convert_url), and a noun (doctype). The pattern is inconsistent, though all names are lowercase and readable.
Five tools is a well-scoped set for a document conversion and URL retrieval server. Each tool addresses a distinct need without unnecessary redundancy.
Core workflows are covered: conversion from uploaded blobs and URLs, format discovery, and web retrieval/search. Minor gap: no explicit output format listing separate from input formats, but the convert tool's outfmt parameter covers it.