lean_multi_attempt
AI agents invoke lean_multi_attempt to trigger actions in Lean Lsp. 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.
Based on the server context (Lean theorem prover interaction) and sibling tools like 'lean_build' and 'lean_completions', this tool likely executes multiple proof attempts in Lean. The 'attempt' suffix suggests running/executing code. Empty description lowers confidence. Categorized as Execute since it likely triggers Lean LSP operations.
From the tool's definition Tool name 'lean_multi_attempt' on a server for 'agentic interaction with the Lean theorem prover via LSP'; description is empty or uninformative.
Documented attack patterns abuse exactly the kind of access lean_multi_attempt gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Lean Lsp, and nothing reaches the server without passing your rules. This is the rule we recommend for lean_multi_attempt:
{
"version": "1",
"default": "deny",
"tools": {
"lean_multi_attempt": {
"limits": [
{
"counter": "lean_multi_attempt_rate",
"window": "minute",
"max": 10,
"scope": "grant"
}
]
}
}
}lean_multi_attempt 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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lean_multi_attempt. It is categorised as a Execute tool in the Lean Lsp MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Lean Lsp MCP server in PolicyLayer and add a rule for lean_multi_attempt: 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 Lean Lsp. Nothing to install.
lean_multi_attempt 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 lean_multi_attempt 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 lean_multi_attempt. 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.
lean_multi_attempt is provided by the Lean Lsp MCP server (project-numina/lean-lsp-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Lean Lsp, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
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22 Lean Lsp tools catalogued and risk-classified — across an index of 43,000+ MCP servers.