List trained models in workspace with metadata
AI agents call list_models to retrieve information from Ultralytics MCP Server without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool performs a simple enumeration/listing of trained models and their metadata. It retrieves information only and has no side effects, fitting the Read category definition of 'retrieves or queries data.' The blast radius is minimal—worst case, an AI agent learns what models exist in the workspace. The low severity reflects that listing workspace contents poses no destructive, financial, or code-execution risk.
From the tool's definition Tool name 'list_models' and description 'List trained models in workspace with metadata' indicate a retrieval operation that queries existing data without modification or execution.
Attacks that exploit this kind of access
List trained models in workspace with metadata. It is categorised as a Read tool in the Ultralytics MCP Server MCP Server, which means it retrieves data without modifying state.
Register the Ultralytics MCP Server MCP server in PolicyLayer and add a rule for list_models: 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 Ultralytics MCP Server. Nothing to install.
list_models 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_models 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_models. 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_models is provided by the Ultralytics MCP Server MCP server (metehanyasar11/ultralytics_mcp_server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Every MCP server has a record like this.
Type a name, get the same breakdown: verified identity, auth posture, risk grade, capabilities, recommended policy.
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