Start or continue a conversation with Gemini about complex coding problems. Supports follow-up questions in the same context. Args: specific_question: The specific question you want answered session_id: Optional session ID to continue a previous conversation problem_description: Detailed descript...
AI agents invoke consult_gemini to trigger actions in Mcp Gemini Assistant. 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.
While the tool primarily retrieves advice (Read-like), it executes requests to an external API/service with user-controlled inputs (question, problem description, code context, file attachments). The file attachment capability and session persistence mean effects are not purely informational.
From the tool's definition Tool initiates conversations with external AI service (Gemini) about code problems, supports file attachments and session management.
Documented attack patterns abuse exactly the kind of access consult_gemini gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Mcp Gemini Assistant, and nothing reaches the server without passing your rules. This is the rule we recommend for consult_gemini:
{
"version": "1",
"default": "deny",
"tools": {
"consult_gemini": {
"limits": [
{
"counter": "consult_gemini_rate",
"window": "minute",
"max": 10,
"scope": "grant"
}
]
}
}
}consult_gemini stays usable, but rate-capped — a runaway agent can't fire it dozens of times a minute. Everything else on the server is denied unless you say otherwise.
Free to start. No card required.
Start or continue a conversation with Gemini about complex coding problems. Supports follow-up questions in the same context. Args: specific_question: The specific question you want answered session_id: Optional session ID to continue a previous conversation problem_description: Detailed description of the coding problem (required for new sessions) code_context: All relevant code - will be cached for the session (required for new sessions) attached_files: Array of file paths to upload and attach to the conversation file_descriptions: Optional object mapping file paths to descriptions additional_context: Additional context, updates, or what changed since last question preferred_approach: Type of assistance needed (solution, review, debug, optimize, explain, follow-up). It is categorised as a Execute tool in the Mcp Gemini Assistant MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Mcp Gemini Assistant MCP server in PolicyLayer and add a rule for consult_gemini: 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 Mcp Gemini Assistant. Nothing to install.
consult_gemini 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 consult_gemini 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 consult_gemini. 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.
consult_gemini is provided by the Mcp Gemini Assistant MCP server (peterkrueck/mcp-gemini-assistant). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Deterministic rules across all 4 Mcp Gemini Assistant tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.
Free to start. No card required.
4 Mcp Gemini Assistant tools catalogued and risk-classified — across an index of 42,500+ MCP servers.