Search team memory, organizational decisions, prior artifacts, and project context across agents. Also known as: search memory, recall decisions, find context, retrieve artifacts, project memory. USE WHEN: user asks about past decisions, context, or knowledge. NEXT: Present relevant results; sugg...
AI agents call query_org_memory to retrieve information from OrgX without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
| Parameter | Type | Required | Description |
|---|---|---|---|
limit | number | — | Maximum number of results to return |
query | string | — | Search query for OrgX memory |
scope | string | — | Optional scope filter for the memory search |
_context | object | — | Client context for conversation tracking (strongly recommended for cross-client continuity) |
Parameters from the server's own tool schema.
Even though query_org_memory only reads data, uncontrolled read access leaks sensitive information and racks up API costs — an agent caught in a retry loop can make thousands of calls a minute without anyone noticing.
Risk signalsAccepts freeform code/query input (query) · High parameter count (20 properties)
Documented attack patterns abuse exactly the kind of access query_org_memory gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and OrgX, and nothing reaches the server without passing your rules. This is the rule we recommend for query_org_memory:
{
"version": "1",
"default": "deny",
"tools": {
"query_org_memory": {}
}
}query_org_memory is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.
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Search team memory, organizational decisions, prior artifacts, and project context across agents. Also known as: search memory, recall decisions, find context, retrieve artifacts, project memory. USE WHEN: user asks about past decisions, context, or knowledge. NEXT: Present relevant results; suggest drill-down with list_entities. Prefer query_org_memory with scope=decisions with a topic query for new prompts, skills, and examples. DO NOT USE: for listing current entities — use list_entities instead. Read-only. It is categorised as a Read tool in the OrgX MCP Server, which means it retrieves data without modifying state.
query_org_memory accepts 4 parameters: limit, query, scope, _context. The full parameter table on this page comes from the server's own tool schema.
Register the OrgX MCP server in PolicyLayer and add a rule for query_org_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 OrgX. Nothing to install.
query_org_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 query_org_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 query_org_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.
query_org_memory is provided by the OrgX MCP server (useorgx/orgx-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Deterministic rules across all 29 OrgX tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.
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29 OrgX tools catalogued and risk-classified — across an index of 42,500+ MCP servers.