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anilist_pick

"What should I watch/read next?" Recommends from your Planning list based on your taste profile. Also works for backlog analysis - "which of my 200 Planning titles should I actually start?" Falls back to top-rated AniList titles if the Planning list is empty. Optionally filter by mood or max epis...

Risk signalsHigh parameter count (10 properties)

Part of the Ani server.

anilist_pick can trigger actions in Ani, with no limits today. PolicyLayer puts allow, deny, and rate-limit rules on every call. Live in minutes.

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AI agents invoke anilist_pick to trigger processes or run actions in Ani. Execute operations can have side effects beyond the immediate call -- triggering builds, sending notifications, or starting workflows. Rate limits and argument validation are essential to prevent runaway execution.

anilist_pick can trigger processes with real-world consequences. An uncontrolled agent might start dozens of builds, send mass notifications, or kick off expensive compute jobs. PolicyLayer enforces rate limits and validates arguments to keep execution within safe bounds.

Execute tools trigger processes. Rate-limit and validate arguments to prevent unintended side effects.

policy.json
{
  "version": "1",
  "default": "deny",
  "tools": {
    "anilist_pick": {
      "limits": [
        {
          "counter": "anilist_pick_rate",
          "window": "minute",
          "max": 10,
          "scope": "grant"
        }
      ]
    }
  }
}

See the full Ani policy for all 55 tools.

Get this rule live on your own Ani server in minutes. PolicyLayer enforces it on every call, before it runs.

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These attack patterns abuse exactly the kind of access anilist_pick gives an agent. Each links to the full case and the policy that stops it:

Browse the full MCP Attack Database →

Every attack above starts with a tool call. PolicyLayer checks each one against your policy first, so anilist_pick only ever does what you allow.

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Other execute tools across the catalogue. The same approach applies to each: rate-limit and validate the arguments.

What does the anilist_pick tool do? +

"What should I watch/read next?" Recommends from your Planning list based on your taste profile. Also works for backlog analysis - "which of my 200 Planning titles should I actually start?" Falls back to top-rated AniList titles if the Planning list is empty. Optionally filter by mood or max episodes. Returns ranked picks with match score, genre alignment, and mood fit.. It is categorised as a Execute tool in the Ani MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.

How do I enforce a policy on anilist_pick? +

Register the Ani MCP server in PolicyLayer and add a rule for anilist_pick: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches Ani. Nothing to install.

What risk level is anilist_pick? +

anilist_pick is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.

Can I rate-limit anilist_pick? +

Yes. Add a rate_limit block to the anilist_pick rule in your PolicyLayer policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.

How do I block anilist_pick completely? +

Set action: deny in the PolicyLayer policy for anilist_pick. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.

What MCP server provides anilist_pick? +

anilist_pick is provided by the Ani MCP server (gavxm/ani-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every Ani tool call.

Deterministic rules across all 55 Ani tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.

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4,600+ MCP servers and 31,000+ tools scanned and risk-classified.

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