AI agents invoke reload_api to trigger actions in Inventor. What it does depends on the arguments the agent supplies, and its effects often reach beyond the immediate call — builds kicked off, notifications sent, workflows started.
This tool dynamically reloads a Python API module from disk at runtime, which is a code execution operation. It triggers the loading and execution of potentially modified Python code, making it an Execute-category action. Misuse could allow arbitrary code execution by swapping the module on disk before reload, giving it high severity.
From the tool's definition Hot-reload inventor_api.py from disk. Use after editing the wrapper
Attacks that exploit this kind of access
Hot-reload inventor_api.py from disk. Use after editing the wrapper —. It is categorised as a Execute tool in the Inventor MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Inventor MCP server in PolicyLayer and add a rule for reload_api: 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 Inventor. Nothing to install.
reload_api is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.
Yes. Add a rate_limit block to the reload_api 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 reload_api. 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.
reload_api is provided by the Inventor MCP server (neonglay/inventor-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Every MCP server has a record like this.
Type a name, get the same breakdown: verified identity, auth posture, risk grade, capabilities, recommended policy.
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