Low Risk

drive_recall

Recall persistent facts and preferences your agents have written. In v1 this returns semantic search results across artifacts; v1.5 will narrow to auto-extracted facts (preferences, decisions, key entities).

Risk signalsAccepts freeform code/query input (query)

Part of the AgentDrive server.

drive_recall 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 drive_recall to retrieve information from AgentDrive 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 drive_recall 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": {
    "drive_recall": {}
  }
}

See the full AgentDrive policy for all 20 tools.

Get this rule live on your own AgentDrive 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 drive_recall gives an agent. Each links to the full case and the policy that stops it:

Browse the full MCP Attack Database →

Every attack above starts with a tool call. PolicyLayer checks each one against your policy first, so drive_recall 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 drive_recall tool do? +

Recall persistent facts and preferences your agents have written. In v1 this returns semantic search results across artifacts; v1.5 will narrow to auto-extracted facts (preferences, decisions, key entities).. It is categorised as a Read tool in the AgentDrive MCP Server, which means it retrieves data without modifying state.

How do I enforce a policy on drive_recall? +

Register the AgentDrive MCP server in PolicyLayer and add a rule for drive_recall: 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 AgentDrive. Nothing to install.

What risk level is drive_recall? +

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

Can I rate-limit drive_recall? +

Yes. Add a rate_limit block to the drive_recall 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 drive_recall completely? +

Set action: deny in the PolicyLayer policy for drive_recall. 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 drive_recall? +

drive_recall is provided by the AgentDrive MCP server (https://mcp.agentdrive.sh/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every AgentDrive tool call.

Deterministic rules across all 20 AgentDrive tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.

Free to start. No card required.

4,600+ MCP servers and 31,000+ tools scanned and risk-classified.

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