stock_recommendation
AI agents call stock_recommendation as a supporting operation in Puch AI MCP Starter workflows.
With an empty description, classification is uncertain. The name 'stock_recommendation' could imply financial advice or stock market recommendations, which might border on Financial category. However, providing a recommendation is not the same as executing a financial transaction (no money movement or financial commitment).
From the tool's definition Tool name is 'stock_recommendation' but description is empty/uninformative. The server description mentions job searching and image processing tools, with no mention of financial tools.
Attacks that exploit this kind of access
stock_recommendation. It is categorised as a Other tool in the Puch AI MCP Starter MCP Server, which means it performs auxiliary operations.
Register the Puch AI MCP Starter MCP server in PolicyLayer and add a rule for stock_recommendation: 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 Puch AI MCP Starter. Nothing to install.
stock_recommendation is a Other tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the stock_recommendation 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 stock_recommendation. 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.
stock_recommendation is provided by the Puch AI MCP Starter MCP server (somnath-chattaraj/mcp-server). 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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