Store a persistent memory. Memories survive across workflow executions and can be recalled later. Categories: fact (known truth), insight (pattern/learning), preference (user preference), outcome (result to track). KG-First: Use this to seed workspace-specific strategy content (ICP criteria, scor...
Part of the Agentled server.
Free to start. No card required.
AI agents call store_memory 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 store_memory 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.
{
"version": "1",
"default": "deny",
"tools": {
"store_memory": {}
}
}See the full Agentled policy for all 119 tools.
These attack patterns abuse exactly the kind of access store_memory gives an agent. Each links to the full case and the policy that stops it:
Other read tools across the catalogue. The same approach applies to each: allow, with a rate cap to control cost.
Store a persistent memory. Memories survive across workflow executions and can be recalled later. Categories: fact (known truth), insight (pattern/learning), preference (user preference), outcome (result to track). KG-First: Use this to seed workspace-specific strategy content (ICP criteria, scoring rubric definitions, investment thesis, brand voice) BEFORE building the workflow steps that need it. Once stored, the AI step references it at runtime via the workspace_memory builtin tool — never hardcoded in the prompt template.. It is categorised as a Read tool in the Agentled MCP Server, which means it retrieves data without modifying state.
Register the Agentled MCP server in PolicyLayer and add a rule for store_memory: 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.
store_memory is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the store_memory 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 store_memory. 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.
store_memory 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.
Deterministic rules across all 119 Agentled 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.