Get personalized music recommendations from your collection based on genre, decade, mood, or similarity to other releases. Supports mood-aware filtering with descriptors like
AI agents call get_recommendations to retrieve information from Discogs MCP Server without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool retrieves and queries data from the user's Discogs music collection to generate personalized recommendations. It has no side effects, does not execute arbitrary code, does not modify or delete data, and does not involve financial transactions. However, it operates on personal music collection data which could reveal user preferences and listening habits (hence medium severity rather than low).
From the tool's definition Tool name 'get_recommendations' and description explicitly states it 'Get[s] personalized music recommendations from your collection' - a retrieval/query operation with no modification, deletion, or execution of external code.
Documented attack patterns abuse exactly the kind of access get_recommendations gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Discogs MCP Server, and nothing reaches the server without passing your rules. This is the rule we recommend for get_recommendations:
{
"version": "1",
"default": "deny",
"tools": {
"get_recommendations": {}
}
} get_recommendations is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.
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Get personalized music recommendations from your collection based on genre, decade, mood, or similarity to other releases. Supports mood-aware filtering with descriptors like. It is categorised as a Read tool in the Discogs MCP Server MCP Server, which means it retrieves data without modifying state.
Register the Discogs MCP Server MCP server in PolicyLayer and add a rule for get_recommendations: 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 Discogs MCP Server. Nothing to install.
get_recommendations 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 get_recommendations 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 get_recommendations. 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.
get_recommendations is provided by the Discogs MCP Server MCP server (rianvdm/discogs-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Discogs MCP Server, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
Free to start. No card required.
20 Discogs MCP Server tools catalogued and risk-classified — across an index of 43,000+ MCP servers.