Update multiple existing entities in the knowledge graph
AI agents use update_entities to create or update resources in Knowledge Graph Memory Server — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Knowledge Graph Memory Server environment.
The tool modifies (rather than creates, executes, or deletes) entities within the knowledge graph. Updates are typically reversible operations—prior data can be restored or overwritten again. This makes it a Write operation.
From the tool's definition Tool name 'update_entities' and description 'Update multiple existing entities in the knowledge graph' indicate modification of existing data in a reversible manner.
Documented attack patterns abuse exactly the kind of access update_entities gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Knowledge Graph Memory Server, and nothing reaches the server without passing your rules. This is the rule we recommend for update_entities:
{
"version": "1",
"default": "deny",
"tools": {
"update_entities": {
"limits": [
{
"counter": "update_entities_rate",
"window": "minute",
"max": 30,
"scope": "grant"
}
]
}
}
}update_entities stays usable, but capped — an agent stuck in a loop can't make hundreds of changes a minute. Everything else on the server is denied unless you say otherwise.
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Update multiple existing entities in the knowledge graph. It is categorised as a Write tool in the Knowledge Graph Memory Server MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the Knowledge Graph Memory Server MCP server in PolicyLayer and add a rule for update_entities: 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 Knowledge Graph Memory Server. Nothing to install.
update_entities is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.
Yes. Add a rate_limit block to the update_entities 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 update_entities. 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.
update_entities is provided by the Knowledge Graph Memory Server MCP server (itseasy21/mcp-knowledge-graph). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Knowledge Graph Memory Server, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
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11 Knowledge Graph Memory Server tools catalogued and risk-classified — across an index of 43,000+ MCP servers.