MCP server providing access to Gravatar API v3.0.0 for avatar and profile services using email hash-based identification
Server has 13 tools with basic naming (verb_noun pattern) and descriptions present. However, critical gaps undermine quality: most parameter descriptions are minimal (1-5 words), input schemas lack type definitions beyond string, output schemas are undocumented, and error handling is absent. Tool names are clear but descriptions average ~40 chars (below 194-char baseline). No evidence of pagination, result limits, or structured output documentation. Composition is reasonable (single-responsibility tools), but parameter validation and LLM-friendly guidance are missing.
Delete an avatar for the authenticated user
Get all email addresses associated with the authenticated user's account
Get all avatars for the authenticated user
Get the authenticated user's profile information
Get a public profile by Gravatar ID or email hash
Get inferred interests for a Gravatar profile by ID
Get a QR code for a Gravatar profile by email hash
Get list of verified account services available on Gravatar
Output schemas completely undocumented. No tool declares what fields it returns, forcing LLMs to guess structure and plan downstream calls blindly.
Parameter descriptions are minimal (1-5 words). E.g., 'avatarId' → 'The ID of the avatar to update' lacks format, constraints, or usage context. LLMs cannot infer valid input ranges or formats.
Input schemas lack type definitions. Parameters are declared as strings with no enum, pattern, or length constraints. E.g., 'service' in search_profiles_by_verified_account has no enum of valid services.
| Scored | Grade | Overall | Spec posture | Rubric |
|---|---|---|---|---|
| 2026-09-23 | F | 35 | 2026-07-28+ | v2 |
Search for Gravatar profiles by verified account service and username
Set which avatar is used for a specific email address
Update an existing avatar for the authenticated user
Update the authenticated user's profile information
Upload a new avatar image for the authenticated user
No error handling guidance. Tools do not document what errors can occur, whether they are retryable, or what the LLM should do next. E.g., delete_avatar offers no recovery path if avatar not found.
Destructive operations (delete_avatar) lack confirmation or dry-run support. Agents can permanently delete avatars without a safety gate.