AI agents use update_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.
The tool updates (modifies) existing workout records reversibly. This is a Write operation as it changes data but does not permanently delete or destroy it. Severity is medium because misuse could corrupt user fitness data or progress tracking, but the blast radius is limited to individual user workout records rather than system-wide or financial impacts.
From the tool's definition Tool name 'update_workout' combined with server context (Hevy fitness tracking API for logging workouts, managing routines, and tracking fitness progress) indicates modification of existing workout data.
Documented attack patterns abuse exactly the kind of access update_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 update_workout:
{
"version": "1",
"default": "deny",
"tools": {
"update_workout": {
"limits": [
{
"counter": "update_workout_rate",
"window": "minute",
"max": 30,
"scope": "grant"
}
]
}
}
}update_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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update_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 update_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.
update_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 update_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 update_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.
update_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.