QR Code Generator — Generate a QR code from a URL, text, or vCard data as a PNG image. [category: generate]
| Name | Required | Description | Default |
|---|---|---|---|
| size | No | Image size in pixels (max 2000) | |
| level | No | Error-correction level | M |
| content | Yes | The URL, text, or vCard data to encode |
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 are neutral (all flags false), so the description carries the behavioral burden. It adds the key trait that output is a PNG image and that content may be URL, text, or vCard. It does not disclose return mechanics (file path vs. binary vs. base64), but for a simple generate tool the disclosed traits are the most relevant. No contradiction with annotations.
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 substantive sentence is tight and front-loaded: verb, resource, input types, and output format all in one line. Minor redundancy exists — 'QR Code Generator' repeats the title, and '[category: generate]' restates the name prefix — but neither is costly.
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 low-complexity tool with 3 params, 100% schema coverage, and a clear one-sentence description, this is nearly complete. The remaining gaps are return-value mechanics (since there is no output schema) and explicit differentiation from generate_barcode, but neither is critical for a simple generator.
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 the baseline is 3. The description's mention of 'URL, text, or vCard data' merely restates the content parameter's schema description rather than adding new meaning (e.g., vCard formatting requirements or error-level semantics).
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 has a specific verb ('Generate'), a distinct resource (QR code), permitted input types (URL, text, vCard), and the output format (PNG image). This distinguishes it clearly from siblings like generate_barcode, generate_certificate, and generate_favicon without needing to inspect their schemas.
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: use this when you need a QR code from URL/text/vCard input. However, there is no explicit guidance about when not to use it or mention of the closest alternative (generate_barcode), which sits directly in the sibling list and could reasonably be confused with a QR generator.
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.
