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Grinv

AniList MCP Server

Get your AniList notifications

get_notifications

Retrieve the authenticated user's AniList notifications for new episodes, activity interactions, follows, and submission updates.

Instructions

[Requires login] Get the authenticated user's AniList notifications: new episodes airing, activity likes/replies/mentions, new followers, thread replies/likes, and media/staff/character data-submission updates. Every item has id, type and a human-readable context/contexts string; the rest of the fields depend on type (e.g. an AIRING item includes media/episode, a FOLLOWING item includes user, an ACTIVITY_MESSAGE item includes message.message — the actual DM text is nested one level inside message).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pageNoPage number for pagination.
perPageNoResults per page (max 25).
type_inNoRestrict to these notification types. Omit to get every type.
markAsReadNoSet true to also reset AniList's unread-notification badge count to 0, as a side effect of this call (the same effect as opening the notifications page on the site). Defaults to false so a routine check doesn't clear the badge.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultsYes
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Discloses side effects (badge reset via markAsRead) and output structure (fields depend on type, nested message.message). 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.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Well-structured, front-loaded with requirement and types, efficient despite length.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given output schema, description fully explains output structure and side effects, leaving no ambiguity.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema covers all parameters with descriptions; description adds little beyond schema, except for markAsRead side effect. Baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

Clearly states it gets authenticated user's notifications, listing specific types. No explicit sibling differentiation, but purpose is unambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Indicates login requirement and explains markAsRead side effect, but lacks explicit guidance on when to use versus other tools.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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