close_position
A write tool on the Alpaca MCP server.
This record as markdown: /tools/cliffsgpt-alpaca-mcp-clone/close-position.md
What close_position does on Alpaca MCP Server
AI agents use close_position to create or update resources in Alpaca MCP Server, usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Alpaca MCP Server environment.
Why close_position is rated Medium
An AI agent can call close_position faster than any human can review: one bad instruction and it creates or modifies resources in Alpaca MCP Server by the hundred, each call as confident as the last.
Attacks that exploit this kind of access
The rule that runs close_position safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Alpaca MCP Server, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For close_position, this is the rule to start with:
close_position 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 Alpaca MCP Server, apply this rule, and every close_position call is checked against it from then on.
Questions about close_position
close_position is a write tool on the Alpaca MCP Server MCP server. It is categorised as a Write tool in the Alpaca MCP Server MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the Alpaca 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 Alpaca MCP Server. Nothing to install.
close_position 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 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.
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.
close_position is provided by the Alpaca MCP Server MCP server (cliffsgpt/alpaca-mcp-clone). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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