Get details of a specific workout by its ID.
AI agents call get_workout to retrieve information from Garmin Workouts MCP Server without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool retrieves and queries specific workout information by ID. It performs a read-only operation that does not create, modify, delete, or execute any actions. No data is altered and the operation is idempotent. This is a straightforward Read category tool with minimal risk if misused by an AI agent.
From the tool's definition Tool name 'get_workout' and description 'Get details of a specific workout by its ID' indicate data retrieval with no side effects.
Documented attack patterns abuse exactly the kind of access get_workout gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Garmin Workouts MCP Server, and nothing reaches the server without passing your rules. This is the rule we recommend for get_workout:
{
"version": "1",
"default": "deny",
"tools": {
"get_workout": {}
}
}get_workout is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.
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Get details of a specific workout by its ID. It is categorised as a Read tool in the Garmin Workouts MCP Server MCP Server, which means it retrieves data without modifying state.
Register the Garmin Workouts MCP Server MCP server in PolicyLayer and add a rule for get_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 Garmin Workouts MCP Server. Nothing to install.
get_workout 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_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 get_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.
get_workout is provided by the Garmin Workouts MCP Server MCP server (st3v/garmin-workouts-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Garmin Workouts MCP Server, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
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10 Garmin Workouts MCP Server tools catalogued and risk-classified — across an index of 43,000+ MCP servers.