Medium Risk

create_teams_plot

Plots a scatter plot with each MLB team Args: data: (pandas.DataFrame) pandas.DataFrame of Fangraphs team data (retrieved through team_batting or team_pitching) x_axis: (str) Stat name to be plotted as the x_axis of the chart y_axis: (str) Stat name to be plotted as the y_axis of the chart title:...

Part of the MLB Stats Server server.

create_teams_plot can modify MLB Stats Server data, with no limits today. PolicyLayer puts allow, deny, and rate-limit rules on every call. Live in minutes.

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AI agents use create_teams_plot to create or modify resources in MLB Stats Server. Write operations carry medium risk because an autonomous agent could trigger bulk unintended modifications. Rate limits prevent a single agent session from making hundreds of changes in rapid succession. Argument validation ensures the agent passes expected values.

Without a policy, an AI agent could call create_teams_plot repeatedly, creating or modifying resources faster than any human could review. PolicyLayer's rate limiting ensures write operations happen at a controlled pace, and argument validation catches malformed or unexpected inputs before they reach MLB Stats Server.

Write tools can modify data. A rate limit prevents runaway bulk operations from AI agents.

policy.json
{
  "version": "1",
  "default": "deny",
  "tools": {
    "create_teams_plot": {
      "limits": [
        {
          "counter": "create_teams_plot_rate",
          "window": "minute",
          "max": 30,
          "scope": "grant"
        }
      ]
    }
  }
}

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These attack patterns abuse exactly the kind of access create_teams_plot gives an agent. Each links to the full case and the policy that stops it:

Browse the full MCP Attack Database →

Every attack above starts with a tool call. PolicyLayer checks each one against your policy first, so create_teams_plot only ever does what you allow.

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Other write tools across the catalogue. The same approach applies to each: rate-limit and validate the arguments.

What does the create_teams_plot tool do? +

Plots a scatter plot with each MLB team Args: data: (pandas.DataFrame) pandas.DataFrame of Fangraphs team data (retrieved through team_batting or team_pitching) x_axis: (str) Stat name to be plotted as the x_axis of the chart y_axis: (str) Stat name to be plotted as the y_axis of the chart title: (str), default = None Optional: Title of the plot. It is categorised as a Write tool in the MLB Stats Server MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.

How do I enforce a policy on create_teams_plot? +

Register the MLB Stats Server MCP server in PolicyLayer and add a rule for create_teams_plot: 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 MLB Stats Server. Nothing to install.

What risk level is create_teams_plot? +

create_teams_plot is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.

Can I rate-limit create_teams_plot? +

Yes. Add a rate_limit block to the create_teams_plot 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 create_teams_plot completely? +

Set action: deny in the PolicyLayer policy for create_teams_plot. 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 create_teams_plot? +

create_teams_plot is provided by the MLB Stats Server MCP server (etweisberg/mlb-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

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