AI agents use create_workout to create or update resources in Hevy — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Hevy environment.
Creating a workout record is a reversible write operation that adds data to a fitness tracking system. It modifies the user's workout log but does not execute arbitrary code, delete data, or move money. Severity is medium because misuse could flood the workout log with spurious entries, but the impact is limited to one user's fitness data and is easily correctable.
From the tool's definition Tool name 'create_workout' and server context (Hevy fitness tracking API for 'logging workouts') indicate data creation.
Documented attack patterns abuse exactly the kind of access create_workout gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Hevy, and nothing reaches the server without passing your rules. This is the rule we recommend for create_workout:
{
"version": "1",
"default": "deny",
"tools": {
"create_workout": {
"limits": [
{
"counter": "create_workout_rate",
"window": "minute",
"max": 30,
"scope": "grant"
}
]
}
}
}create_workout stays usable, but capped — an agent stuck in a loop can't make hundreds of changes a minute. Everything else on the server is denied unless you say otherwise.
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create_workout. It is categorised as a Write tool in the Hevy MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the Hevy MCP server in PolicyLayer and add a rule for create_workout: 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 Hevy. Nothing to install.
create_workout is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.
Yes. Add a rate_limit block to the create_workout 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 create_workout. 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.
create_workout is provided by the Hevy MCP server (tomtorggler/hevy-mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Hevy, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
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17 Hevy tools catalogued and risk-classified — across an index of 43,000+ MCP servers.