This record as markdown: /tools/app-businys-mcp-server/create-exercise.md
What create_exercise does on Businys
AI agents use create_exercise to create or update resources in Businys, usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Businys environment.
Why create_exercise is rated Medium
This tool creates a new exercise record, which is a reversible write operation. There is no code execution, financial transaction, or data deletion involved. The blast radius is minimal—a mistaken exercise creation can be easily corrected or deleted by the user. Low severity because the action is non-destructive and domain-specific to fitness data management.
From the tool's definition Tool name 'create_exercise' and description 'Create a custom exercise' explicitly indicate data creation.
Attacks that exploit this kind of access
The rule that runs create_exercise safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Businys, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For create_exercise, this is the rule to start with:
create_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.
The button opens the PolicyLayer dashboard: create your workspace, connect Businys, apply this rule, and every create_exercise call is checked against it from then on.
Questions about create_exercise
Create a custom exercise. Requires a name. It is categorised as a Write tool in the Businys MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the Businys MCP server in PolicyLayer and add a rule for create_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 Businys. Nothing to install.
create_exercise 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 create_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.
Set action: deny in the PolicyLayer policy for create_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.
create_exercise is provided by the Businys MCP server (@businys/mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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