Get the parent run of a nested run. Returns None if the run has no parent.
AI agents call get_parent_run to retrieve information from MLflow MCP Server without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool queries run hierarchy metadata from the MLflow tracking server and returns read-only information. It has no side effects—it does not create, modify, delete, or execute operations. The blast radius of misuse is minimal; an attacker could learn about experiment structure but cannot alter or destroy data.
From the tool's definition Tool 'get_parent_run' retrieves information about a parent run relationship. The description explicitly states it 'returns' data with no indication of modification, creation, or deletion. This is a pure query/lookup operation.
Documented attack patterns abuse exactly the kind of access get_parent_run gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and MLflow MCP Server, and nothing reaches the server without passing your rules. This is the rule we recommend for get_parent_run:
{
"version": "1",
"default": "deny",
"tools": {
"get_parent_run": {}
}
}get_parent_run is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.
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Get the parent run of a nested run. Returns None if the run has no parent. It is categorised as a Read tool in the MLflow MCP Server MCP Server, which means it retrieves data without modifying state.
Register the MLflow MCP Server MCP server in PolicyLayer and add a rule for get_parent_run: 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 MLflow MCP Server. Nothing to install.
get_parent_run 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_parent_run 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_parent_run. 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_parent_run is provided by the MLflow MCP Server MCP server (kkruglik/mlflow-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from MLflow 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.
40 MLflow MCP Server tools catalogued and risk-classified — across an index of 43,000+ MCP servers.