AI agents call get_training_plan to retrieve information from MCPacer without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool retrieves a training plan—a read operation with no capacity to modify, delete, or execute external actions. The blast radius of misuse is minimal; an AI agent could only access personal training data it should reasonably have permission to view. No destructive, financial, or code-execution risk.
From the tool's definition Tool name 'get_training_plan' indicates retrieval of training plan data. Server context (Strava-connected running coach) and sibling tools like 'get_activities', 'get_activity_by_id', and 'get_activity_description' all follow read-only retrieval patterns.
Documented attack patterns abuse exactly the kind of access get_training_plan gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and MCPacer, and nothing reaches the server without passing your rules. This is the rule we recommend for get_training_plan:
{
"version": "1",
"default": "deny",
"tools": {
"get_training_plan": {}
}
}get_training_plan is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.
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get_training_plan. It is categorised as a Read tool in the MCPacer MCP Server, which means it retrieves data without modifying state.
Register the MCPacer MCP server in PolicyLayer and add a rule for get_training_plan: 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 MCPacer. Nothing to install.
get_training_plan 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_training_plan 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_training_plan. 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_training_plan is provided by the MCPacer MCP server (wernerpe/mcpacer). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from MCPacer, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
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32 MCPacer tools catalogued and risk-classified — across an index of 43,000+ MCP servers.