add_exercise · Arvo MCP Server MCP: Risk & Policy

WHAT IT DOES

What add_exercise does on Arvo MCP Server

AI agents use add_exercise to create or update resources in Arvo MCP Server — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Arvo MCP Server environment.

WHY IT NEEDS A POLICY

Why add_exercise needs a policy

This tool modifies user data by adding a new exercise entry, which qualifies as Write category. The severity is medium because while this is reversible and non-destructive, incorrect exercise additions could clutter workout logs or require manual cleanup. The confidence is high (0.85) because the name and description clearly indicate data creation/modification without destructive or executable side effects.

From the tool's definition The tool name 'add_exercise' and description 'Add a new exercise to today' indicate it creates new data (a workout exercise entry) in the fitness tracking system. This is a reversible modification that adds information to the user's workout log.

Attacks that exploit this kind of access

Recommended rule Ready

Verdict

add_exercise Rate-limited

add_exercise 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.

View as policy code

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "add_exercise": {
      "limits": [
        {
          "counter": "add_exercise_rate",
          "window": "minute",
          "max": 30,
          "scope": "grant"
        }
      ]
    }
  }
}

LIMIT THIS TOOL →

Instant setup, no code required.

PolicyLayer is an MCP gateway: every tool call is checked against your rule before it reaches Arvo MCP Server, so you can run agents against it safely.

FAQ

Questions about add_exercise

What does the add_exercise tool do? +

Add a new exercise to today. It is categorised as a Write tool in the Arvo MCP Server MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.

How do I enforce a policy on add_exercise? +

Register the Arvo MCP Server MCP server in PolicyLayer and add a rule for add_exercise: 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 Arvo MCP Server. Nothing to install.

What risk level is add_exercise? +

add_exercise is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.

Can I rate-limit add_exercise? +

Yes. Add a rate_limit block to the add_exercise 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.

How do I block add_exercise completely? +

Set action: deny in the PolicyLayer policy for add_exercise. 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.

What MCP server provides add_exercise? +

add_exercise is provided by the Arvo MCP Server MCP server (khaoss85/arvo-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.