Validate code against MMLA specification. 🚨 核心修正 1: 絕對門禁檢查 只有狀態為 GREEN 的節點才能進行代碼驗證 Args: code: The Python code to validate node_id: The MMLA node ID to validate against use_agentic_loop: If True, use Agentic Loop with auto-fix (up to 16 retries) Returns: JSON string with validation results
AI agents invoke mmla_validate_code to trigger actions in Bluemouse. 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.
The tool validates Python code against a specification and can trigger an agentic loop with auto-fix retries. While framed as validation, it actively processes and potentially modifies/executes code logic through an automated loop (up to 16 retries).
From the tool's definition Validate code against MMLA specification... use_agentic_loop: If True, use Agentic Loop with auto-fix (up to 16 retries)
Documented attack patterns abuse exactly the kind of access mmla_validate_code gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Bluemouse, and nothing reaches the server without passing your rules. This is the rule we recommend for mmla_validate_code:
{
"version": "1",
"default": "deny",
"tools": {
"mmla_validate_code": {
"limits": [
{
"counter": "mmla_validate_code_rate",
"window": "minute",
"max": 10,
"scope": "grant"
}
]
}
}
}mmla_validate_code 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.
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Validate code against MMLA specification. 🚨 核心修正 1: 絕對門禁檢查 只有狀態為 GREEN 的節點才能進行代碼驗證 Args: code: The Python code to validate node_id: The MMLA node ID to validate against use_agentic_loop: If True, use Agentic Loop with auto-fix (up to 16 retries) Returns: JSON string with validation results. It is categorised as a Execute tool in the Bluemouse MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Bluemouse MCP server in PolicyLayer and add a rule for mmla_validate_code: 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 Bluemouse. Nothing to install.
mmla_validate_code 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 mmla_validate_code 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 mmla_validate_code. 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.
mmla_validate_code is provided by the Bluemouse MCP server (peijun1700/bluemouse). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Deterministic rules across all 8 Bluemouse tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.
Free to start. No card required.
8 Bluemouse tools catalogued and risk-classified — across an index of 42,500+ MCP servers.