model_match_recommend

Return the single best-fit AI model for a task, with a plain-English rationale covering quality, latency, and cost trade-offs.

Server Scan Your Ai Toolkit sakthivelchan89/scan_your_ai_toolkit
Category Read
Risk class Low
Parameters 00 required

What model_match_recommend does on Scan Your Ai Toolkit

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

Why model_match_recommend needs a policy

This tool retrieves and analyzes data to generate a recommendation. It produces informational output about AI models suitable for a given task, considering quality, latency, and cost factors. There are no side effects, state changes, code execution, or irreversible actions. The tool reads or queries available model information and returns a suggestion, fitting the Read category.

From the tool's definition The tool 'model_match_recommend' returns recommendations based on analysis of task requirements against model characteristics.

Questions about model_match_recommend

What does the model_match_recommend tool do? +

Return the single best-fit AI model for a task, with a plain-English rationale covering quality, latency, and cost trade-offs. It is categorised as a Read tool in the Scan Your Ai Toolkit MCP Server, which means it retrieves data without modifying state.

How do I enforce a policy on model_match_recommend? +

Register the Scan Your Ai Toolkit MCP server in PolicyLayer and add a rule for model_match_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 Scan Your Ai Toolkit. Nothing to install.

What risk level is model_match_recommend? +

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

Can I rate-limit model_match_recommend? +

Yes. Add a rate_limit block to the model_match_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.

How do I block model_match_recommend completely? +

Set action: deny in the PolicyLayer policy for model_match_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.

What MCP server provides model_match_recommend? +

model_match_recommend is provided by the Scan Your Ai Toolkit MCP server (sakthivelchan89/scan_your_ai_toolkit). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

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