list_self_favorites
List the current user's favorite recipes.
This record as markdown: /tools/nikopol666-mealie-mcp/list-self-favorites.md
What list_self_favorites does on Mealie MCP Server
AI agents call list_self_favorites to retrieve information from Mealie MCP Server without modifying anything. It is typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
Why list_self_favorites is rated Low
This tool retrieves and queries favorite recipe data belonging to the current user with no side effects, creation, modification, or deletion of data. It is a simple read operation with minimal risk even if misused by an AI agent.
From the tool's definition Tool name 'list_self_favorites' and description 'List the current user's favorite recipes' clearly indicate data retrieval with no modifications.
Attacks that exploit this kind of access
The rule that runs list_self_favorites safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Mealie MCP Server, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For list_self_favorites, this is the rule to start with:
list_self_favorites is read-only, so it stays allowed. Everything else on the server is denied unless you say otherwise.
The button opens the PolicyLayer dashboard: create your workspace, connect Mealie MCP Server, apply this rule, and every list_self_favorites call is checked against it from then on.
Questions about list_self_favorites
List the current user's favorite recipes. It is categorised as a Read tool in the Mealie MCP Server MCP Server, which means it retrieves data without modifying state.
Register the Mealie MCP Server MCP server in PolicyLayer and add a rule for list_self_favorites: 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 Mealie MCP Server. Nothing to install.
list_self_favorites 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 list_self_favorites 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 list_self_favorites. 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.
list_self_favorites is provided by the Mealie MCP Server MCP server (nikopol666/mealie-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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