Search for movies by title or keywords
AI agents call search_movies to retrieve information from Tmdb without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool performs a straightforward read operation against TMDB's movie database. It retrieves matching movie information based on search criteria but does not create, modify, delete, or execute any operations. The blast radius of misuse is minimal—an agent could only retrieve unwanted movie information, which has no security or operational impact.
From the tool's definition Tool name 'search_movies' and description 'Search for movies by title or keywords' indicate a query operation that retrieves data without modifying or executing actions. No side effects or external operations are triggered.
Documented attack patterns abuse exactly the kind of access search_movies gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Tmdb, and nothing reaches the server without passing your rules. This is the rule we recommend for search_movies:
{
"version": "1",
"default": "deny",
"tools": {
"search_movies": {}
}
}search_movies is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.
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Search for movies by title or keywords. It is categorised as a Read tool in the Tmdb MCP Server, which means it retrieves data without modifying state.
Register the Tmdb MCP server in PolicyLayer and add a rule for search_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 Tmdb. Nothing to install.
search_movies is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the search_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.
Set action: deny in the PolicyLayer policy for search_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.
search_movies is provided by the Tmdb MCP server (laksh-star/mcp-server-tmdb). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Tmdb, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
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24 Tmdb tools catalogued and risk-classified — across an index of 43,000+ MCP servers.