Low Risk

search_memories

Search memories by natural language query and/or category. Returns matching memories sorted by confidence. Use to find relevant stored knowledge. KG-First: Call this BEFORE generating AI-step prompts with business-specific content to check whether workspace strategy (ICP, thesis, rubric) is alrea...

Risk signalsAccepts freeform code/query input (query)

Part of the Agentled server.

search_memories 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 search_memories to retrieve information from Agentled 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 search_memories 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": {
    "search_memories": {}
  }
}

See the full Agentled policy for all 119 tools.

Get this rule live on your own Agentled 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 search_memories 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 search_memories 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 search_memories tool do? +

Search memories by natural language query and/or category. Returns matching memories sorted by confidence. Use to find relevant stored knowledge. KG-First: Call this BEFORE generating AI-step prompts with business-specific content to check whether workspace strategy (ICP, thesis, rubric) is already stored. Reference found memories at runtime instead of inlining them in prompt strings.. It is categorised as a Read tool in the Agentled MCP Server, which means it retrieves data without modifying state.

How do I enforce a policy on search_memories? +

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

What risk level is search_memories? +

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

Can I rate-limit search_memories? +

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

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

search_memories is provided by the Agentled MCP server (@agentled/mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every Agentled tool call.

Deterministic rules across all 119 Agentled tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.

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