AI agents call deal_show to retrieve information from Llama without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool retrieves deal information from the Llama Ventures platform by UUID. It is a read-only query operation that returns data without creating, modifying, deleting, or executing any operations. The incomplete description ('Includes status,') does not suggest any write, execute, or destructive capabilities.
From the tool's definition Tool name 'deal_show' and description 'Get the full canonical record for one deal by uuid' indicate a retrieval operation with no modification or side effects.
Attacks that exploit this kind of access
Get the full canonical record for one deal by uuid. Includes status,. It is categorised as a Read tool in the Llama MCP Server, which means it retrieves data without modifying state.
Register the Llama MCP server in PolicyLayer and add a rule for deal_show: 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 Llama. Nothing to install.
deal_show is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the deal_show 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 deal_show. 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.
deal_show is provided by the Llama MCP server (llama-ventures/llama-cli). 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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