Fetch URL — Fetch the raw (decoded) HTML of a public web page at a user-provided http(s) URL. SSRF-guarded, http/https only, 10 MB body cap, robots-aware. [category: web]
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | http(s) URL to fetch | |
| timeout_ms | No | Optional fetch timeout override in milliseconds. | |
| user_agent | No | Optional custom User-Agent header. | |
| acknowledge_robots | No | Business+ only: proceed even when robots.txt disallows the page. |
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 disclose readOnlyHint=true and openWorldHint=true, so the safety profile is covered. The description adds useful behavioral constraints beyond annotations: SSRF-guarded, http/https only, 10 MB body cap, robots-aware, and decoded output. It doesn't detail robots-disallow failure behavior, but the schema's acknowledge_robots parameter partially covers that.
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 compact and front-loaded: the action and object appear immediately, followed by a dense but readable constraint clause. Every sentence earns its place, with no filler or redundancy.
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?
With no output schema, the description still conveys the returned artifact ('raw (decoded) HTML') and key operational limits. It omits behavior on non-200 responses, redirects, and exact robots.txt handling, but the schema and annotations cover enough that an agent can invoke it correctly. A small gap, not a major one.
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 every parameter already carries a meaningful description. The tool description contributes contextual constraints for the URL (public, http(s), size cap) but does not add per-parameter semantics beyond the schema. Baseline 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 states a specific verb ('Fetch'), resource ('raw (decoded) HTML of a public web page at a user-provided http(s) URL'), and clear scope constraints. This distinguishes it from siblings like web_scrape_page or web_extract_table, which imply structured extraction rather than raw HTML retrieval.
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?
Usage is implied through 'raw (decoded) HTML' and 'public web page', and the constraints 'http/https only' and 'robots-aware' set boundaries. However, the description never explicitly says when to choose this tool over alternatives such as web_scrape_page or convert_url_to_pdf, so the guidance is adequate but not explicit.
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.
Multiple tool pairs are near-identical: octopus_mkdir/octopus_make_folder and octopus_move/octopus_move_file are literal duplicates, analyze_hash/generate_hash both compute hashes, convert_word_to_pdf overlaps convert_document, and photo_compress/photo_compress_to_size plus pdf_thumbnails/pdf_to_images have fuzzy boundaries. The descriptions are detailed and cross-reference each other helpfully, but at 144 tools an agent will regularly misselect.
The dominant {category}_{verb}_{object} snake_case pattern (pdf_*, photo_*, convert_*, analyze_*, media_*) is largely consistent and predictable. However, outliers like chatwithyourpdf and describe_image break the category-prefix convention, and the octopus namespace mixes bare verbs (read, write, mkdir) with verb_noun forms (make_folder, move_file, search_meta) inconsistently.
144 tools is an extreme count for any MCP server. The broad scope (PDF, photo, video, audio, conversion, analysis, generation, file storage, web, e-sign) justifies some volume, but the count is inflated by batch and inspect variants (pdf_to_excel + batch + inspect), duplicate tools, and overlapping converters. An agent faces an overwhelming selection surface.
Per-domain coverage is remarkably deep: PDF spans merge/split/compress/protect/unlock/metadata/OCR/watermark and bidirectional conversion; photo covers editing, format conversion, face handling, OCR, and collage; file storage has full CRUD plus search. Minor gaps exist (no audio transcription, no video metadata editing, no deletion of PDF pages is actually covered via pdf_delete_pages) but the surface has no dead ends for its declared domains.
