close_position

close_position

Server HyperLiquid MCP Server talkincode/hyperliquid-mcp-python
Category Write
Risk class Medium
Parameters 00 required

What close_position does on HyperLiquid MCP Server

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

Why close_position needs a policy

An AI agent can call close_position faster than any human can review — one bad instruction and it creates or modifies resources in HyperLiquid MCP Server by the hundred, each call as confident as the last.

Questions about close_position

What does the close_position tool do? +

close_position. It is categorised as a Write tool in the HyperLiquid 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 close_position? +

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

What risk level is close_position? +

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

Can I rate-limit close_position? +

Yes. Add a rate_limit block to the close_position 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 close_position completely? +

Set action: deny in the PolicyLayer policy for close_position. 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 close_position? +

close_position is provided by the HyperLiquid MCP Server MCP server (talkincode/hyperliquid-mcp-python). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

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