Low Risk

fetch_played_movies

fetch_played_movies

How to control fetch_played_movies ↓

AI agents call fetch_played_movies to retrieve information from Trakt without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.

Low Risk

The tool retrieves viewing history data from the user's Trakt account. No data is created, modified, deleted, or executed. While the description is empty, the naming convention and context from sibling fetch-based tools strongly indicate this is a simple data retrieval operation with minimal security risk.

From the tool's definition Tool name 'fetch_played_movies' uses the verb 'fetch', which is a read operation that retrieves data without modification.

Documented attack patterns abuse exactly the kind of access fetch_played_movies gives an agent:

PolicyLayer is an MCP gateway — it sits between your AI agents and Trakt, and nothing reaches the server without passing your rules. This is the rule we recommend for fetch_played_movies:

policy.json
{
  "version": "1",
  "default": "deny",
  "tools": {
    "fetch_played_movies": {}
  }
}

fetch_played_movies is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.

  1. Create a free account and register Trakt — nothing to install.
  2. Add this policy — paste it, or build it visually.
  3. Point your MCP client (Claude, Cursor, anything) at your gateway URL.
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Go deeper

What does the fetch_played_movies tool do? +

fetch_played_movies. It is categorised as a Read tool in the Trakt MCP Server, which means it retrieves data without modifying state.

How do I enforce a policy on fetch_played_movies? +

Register the Trakt MCP server in PolicyLayer and add a rule for fetch_played_movies: 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 Trakt. Nothing to install.

What risk level is fetch_played_movies? +

fetch_played_movies is a Read tool with low risk. Read-only tools are generally safe to allow by default.

Can I rate-limit fetch_played_movies? +

Yes. Add a rate_limit block to the fetch_played_movies 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 fetch_played_movies completely? +

Set action: deny in the PolicyLayer policy for fetch_played_movies. 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 fetch_played_movies? +

fetch_played_movies is provided by the Trakt MCP server (wwiens/trakt_mcpserver). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every Trakt tool call.

Deterministic rules across all 77 Trakt tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.

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77 Trakt tools catalogued and risk-classified — across an index of 42,500+ MCP servers.

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