Critical Risk →

delete_observations

Delete specific observations from entities in the knowledge graph

How to control delete_observations ↓

What delete_observations does on Elasticsearch Knowledge Graph for MCP

AI agents call delete_observations to permanently remove resources in Elasticsearch Knowledge Graph for MCP — typically in cleanup and lifecycle workflows. It does its job in a single call, and there is no undo.

Critical Risk

Why delete_observations needs a policy

This tool permanently removes observations, which cannot be undone. Deletion is the canonical destructive operation. While not financial or code-execution, the ability to irreversibly erase stored knowledge graph data represents a high-severity risk if an AI agent misuses it to corrupt or sanitize records.

From the tool's definition Tool name explicitly uses 'delete' and description states 'Delete specific observations from entities' — irreversible removal of data from the knowledge graph.

Documented attack patterns abuse exactly the kind of access delete_observations gives an agent:

How to control delete_observations

PolicyLayer is an MCP gateway — it sits between your AI agents and Elasticsearch Knowledge Graph for MCP, and nothing reaches the server without passing your rules. This is the rule we recommend for delete_observations:

policy.json
{
  "version": "1",
  "default": "deny",
  "hide": [
    "delete_observations"
  ]
}

delete_observations disappears from the agent's tool list entirely, and any attempt to call it is denied. The rest of the server keeps working.

  1. Create a free account and register Elasticsearch Knowledge Graph for MCP — nothing to install.
  2. Add this policy — paste it, or build it visually.
  3. Point your MCP client (Claude, Cursor, anything) at your gateway URL.
RESTRICT THIS TOOL →

Free to start. No card required.

Related tools and policies

Go deeper

Questions about delete_observations

What does the delete_observations tool do? +

Delete specific observations from entities in the knowledge graph. It is categorised as a Destructive tool in the Elasticsearch Knowledge Graph for MCP MCP Server, which means it can permanently delete or destroy data. Block by default and require explicit approval.

How do I enforce a policy on delete_observations? +

Register the Elasticsearch Knowledge Graph for MCP server in PolicyLayer and add a rule for delete_observations: 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 Elasticsearch Knowledge Graph for MCP. Nothing to install.

What risk level is delete_observations? +

delete_observations is a Destructive tool with critical risk. Critical-risk tools should be blocked by default and only enabled with explicit human approval.

Can I rate-limit delete_observations? +

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

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

delete_observations is provided by the Elasticsearch Knowledge Graph for MCP server (j3k0/mcp-brain-tools). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every Elasticsearch Knowledge Graph for MCP tool call.

Start from Elasticsearch Knowledge Graph for MCP, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.

Free to start. No card required.

23 Elasticsearch Knowledge Graph for MCP tools catalogued and risk-classified — across an index of 43,000+ MCP servers.

// GET IN TOUCH

Have a question or want to learn more? Send us a message.

Message sent.

We'll get back to you soon.