AI agents call get_plan_context 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.
The 'get_' prefix and contextual placement among retrieval tools strongly suggests this retrieves plan-related data without modification. Although the description is empty (lowering confidence slightly), the naming pattern and sibling tools consistently point to a query/fetch operation with no side effects. No data creation, modification, deletion, code execution, or financial impact is implied.
From the tool's definition Tool name 'get_plan_context' combined with server's function as a running coach providing 'personalized training plans' and 'progress tracking' indicates a retrieval operation.
Documented attack patterns abuse exactly the kind of access get_plan_context 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_plan_context:
{
"version": "1",
"default": "deny",
"tools": {
"get_plan_context": {}
}
}get_plan_context is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.
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get_plan_context. 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_plan_context: 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_plan_context 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_plan_context 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_plan_context. 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_plan_context 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.