Invoke the headless Gemini CLI with a prompt plus a separate context block. Stateless — each call is an independent turn. The context is prepended to the prompt inside a <context> tag. Runs in the MCP server
AI agents invoke gemini_prompt_with_context to trigger actions in Geminicli. 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 executes external operations (invoking Gemini CLI and sending queries to Google's Gemini models) based on user-supplied arguments. While the immediate output is text and appears read-only on its surface, it is fundamentally an Execute action because: (1) it invokes an external service whose behavior depends entirely on the prompt content, (2) the context parameter allows injection of arbitrary information…
From the tool's definition Tool invokes the headless Gemini CLI with a prompt plus context, runs in the MCP server — this is a code/command execution interface that triggers an external operation (Gemini API call) whose effects depend on the prompt and context arguments.
Attacks that exploit this kind of access
Invoke the headless Gemini CLI with a prompt plus a separate context block. Stateless — each call is an independent turn. The context is prepended to the prompt inside a <context> tag. Runs in the MCP server. It is categorised as a Execute tool in the Geminicli MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Geminicli MCP server in PolicyLayer and add a rule for gemini_prompt_with_context: 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 Geminicli. Nothing to install.
gemini_prompt_with_context 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 gemini_prompt_with_context 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 gemini_prompt_with_context. 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.
gemini_prompt_with_context is provided by the Geminicli MCP server (trevoraspencer/geminicli-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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