Send native MON or ERC20 tokens to another address
AI agents use send_transaction to commit financial operations through Monad MCP Server — usually the final step of a payment, billing, or trading workflow. A call moves real money.
This tool transfers cryptocurrency assets (native MON tokens or ERC20 tokens) to another address, which constitutes a financial operation that moves monetary value. Misuse could result in irreversible loss of funds, warranting a critical severity rating.
From the tool's definition Send native MON or ERC20 tokens to another address
Attacks that exploit this kind of access
Send native MON or ERC20 tokens to another address. It is categorised as a Financial tool in the Monad MCP Server MCP Server, which means it involves financial transactions. Block by default and require explicit approval.
Register the Monad MCP Server MCP server in PolicyLayer and add a rule for send_transaction: 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 Monad MCP Server. Nothing to install.
send_transaction is a Financial tool with critical risk. Critical-risk tools should be blocked by default and only enabled with explicit human approval.
Yes. Add a rate_limit block to the send_transaction 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 send_transaction. 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.
send_transaction is provided by the Monad MCP Server MCP server (tairon-ai/monad-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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