This record as markdown: /tools/io-github-kivanccakmak-yaver/models-recommend.md
What models_recommend does on Yaver
AI agents call models_recommend to retrieve information from Yaver without modifying anything. It is typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
Why models_recommend is rated Low
This tool retrieves and analyzes hardware specifications to provide recommendations. It has no side effects—it does not create, modify, delete, execute code, or move money. It is purely an informational read operation that queries local hardware state and returns suggestions.
From the tool's definition Tool name 'models_recommend' and description 'Recommend models based on your hardware (RAM, GPU)' indicate a query/recommendation operation that reads hardware information and returns matching model suggestions.
Attacks that exploit this kind of access
The rule that runs models_recommend safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Yaver, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For models_recommend, this is the rule to start with:
models_recommend 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 Yaver, apply this rule, and every models_recommend call is checked against it from then on.
Questions about models_recommend
Recommend models based on your hardware (RAM, GPU). It is categorised as a Read tool in the Yaver MCP Server, which means it retrieves data without modifying state.
Register the Yaver MCP server in PolicyLayer and add a rule for models_recommend: 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 Yaver. Nothing to install.
models_recommend 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 models_recommend 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 models_recommend. 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.
models_recommend is provided by the Yaver MCP server (yaver-cli). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
More on Yaver, and thousands of servers like it.
This server
Across the catalogue