anilist-mcp: AniList MCP server for accessing anime and manga data

by yuna0x0 · MCP Server · ★ 92

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

How to install anilist-mcp

git clone https://github.com/yuna0x0/anilist-mcp.git
docker pull ghcr.io/yuna0x0/anilist-mcp

Taken from the project's README on GitHub.

Security audit verdict: SAFE · quality 65/100

None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours.

The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.

aianilistanimeapillmmangamcpmodel-context-protocol

Quick Facts

Stars92
Forks19
LanguageTypeScript
CategoryMCP Server
LicenseMIT
Quality Score65/100
Open Issues3
Last Updated2026-07-13
Created2025-03-20
Platformsmcp, node
Est. Tokens~13k

About anilist-mcp

AniList MCP Server A Model Context Protocol (MCP) server that interfaces with the AniList API, allowing LLM clients to access and interact with anime, manga, character, staff, and user data from AniList.

Compatible Skills

These tools work well together with anilist-mcp for enhanced workflows:

  • square-mcp-server — semantic(0.64)+same_lang+similar_pop+shared_platform (57%)
  • mcp-server — semantic(0.58)+same_lang+similar_pop+shared_platform (55%)
  • mcp-uptime-kuma — semantic(0.54)+same_lang+similar_pop+shared_platform (54%)

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How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. It is a first-layer scan, not a manual audit — we say so rather than overstate it.

The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.

Sources & who's responsible:

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