Count the number of tokens in content.
AI agents call gemini_count_tokens_tool to retrieve information from MCP Gemini without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
Counting tokens is a purely informational operation with no side effects. It retrieves metadata about input without altering state, triggering external operations, or moving resources. This is a textbook Read category tool.
From the tool's definition Tool name and description indicate it 'count[s] the number of tokens in content' — a query operation that inspects but does not modify, create, or execute anything.
Attacks that exploit this kind of access
Count the number of tokens in content. It is categorised as a Read tool in the MCP Gemini MCP Server, which means it retrieves data without modifying state.
Register the MCP Gemini MCP server in PolicyLayer and add a rule for gemini_count_tokens_tool: 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. Nothing to install.
gemini_count_tokens_tool 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 gemini_count_tokens_tool 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_count_tokens_tool. 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_count_tokens_tool is provided by the MCP Gemini MCP server (mcp-gemini-crunchtools). 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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