Low Risk

recommend_bundle_submission

Get an actionable bundle submission recommendation for a specific borrower or current market conditions. Returns the best builder to target, expected inclusion probability, and a human-readable reason based on live relay telemetry. Pair with monitor_crossing_candidates — identify a hot candidate,...

Part of the MEV Intelligence server.

recommend_bundle_submission is read-only, but an agent in a loop can still rack up calls and cost. PolicyLayer caps every call before it runs. Live in minutes.

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AI agents call recommend_bundle_submission to retrieve information from MEV Intelligence without modifying any data. This is common in research, monitoring, and reporting workflows where the agent needs context before taking action. Because read operations don't change state, they are generally safe to allow without restrictions -- but you may still want rate limits to control API costs.

Even though recommend_bundle_submission only reads data, uncontrolled read access can leak sensitive information or rack up API costs. An agent caught in a retry loop could make thousands of calls per minute. A rate limit gives you a safety net without blocking legitimate use.

Read-only tools are safe to allow by default. No rate limit needed unless you want to control costs.

policy.json
{
  "version": "1",
  "default": "deny",
  "tools": {
    "recommend_bundle_submission": {}
  }
}

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Get this rule live on your own MEV Intelligence server in minutes. PolicyLayer enforces it on every call, before it runs.

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These attack patterns abuse exactly the kind of access recommend_bundle_submission gives an agent. Each links to the full case and the policy that stops it:

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Every attack above starts with a tool call. PolicyLayer checks each one against your policy first, so recommend_bundle_submission only ever does what you allow.

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Other read tools across the catalogue. The same approach applies to each: allow, with a rate cap to control cost.

What does the recommend_bundle_submission tool do? +

Get an actionable bundle submission recommendation for a specific borrower or current market conditions. Returns the best builder to target, expected inclusion probability, and a human-readable reason based on live relay telemetry. Pair with monitor_crossing_candidates — identify a hot candidate, then call this to decide WHERE to submit your bundle.. It is categorised as a Read tool in the MEV Intelligence MCP Server, which means it retrieves data without modifying state.

How do I enforce a policy on recommend_bundle_submission? +

Register the MEV Intelligence MCP server in PolicyLayer and add a rule for recommend_bundle_submission: 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 MEV Intelligence. Nothing to install.

What risk level is recommend_bundle_submission? +

recommend_bundle_submission is a Read tool with low risk. Read-only tools are generally safe to allow by default.

Can I rate-limit recommend_bundle_submission? +

Yes. Add a rate_limit block to the recommend_bundle_submission 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.

How do I block recommend_bundle_submission completely? +

Set action: deny in the PolicyLayer policy for recommend_bundle_submission. 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.

What MCP server provides recommend_bundle_submission? +

recommend_bundle_submission is provided by the MEV Intelligence MCP server (https://mev.advalorem.io/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every MEV Intelligence tool call.

Deterministic rules across all 9 MEV Intelligence tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.

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