index_embeddings

Index all entities for semantic search. Call this after adding entities to enable semantic search. Requires embedding provider.

SERVEREnhanced Knowledge Graph Memory Server SOURCEdanielsimonjr/memory-mcp

Low RISK CLASS

Category Read

Parameters 00 required

Recommended Allowedsee the rule below

Registry record Grade F, identity unverified Pull the record →

This record as markdown: /tools/danielsimonjr-memory-mcp/index-embeddings.md

WHAT IT DOES

What index_embeddings does on Enhanced Knowledge Graph Memory Server

AI agents call index_embeddings to retrieve information from Enhanced Knowledge Graph Memory Server without modifying anything. It is typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.

RISK

Why index_embeddings is rated Low

Even though index_embeddings 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.

Attacks that exploit this kind of access

RECOMMENDED RULE

The rule that runs index_embeddings safely

PolicyLayer is an MCP gateway: it sits between your AI agents and Enhanced Knowledge Graph Memory Server, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For index_embeddings, this is the rule to start with:

index_embeddings Allowed

index_embeddings is read-only, so it stays allowed. Everything else on the server is denied unless you say otherwise.

View as policy code

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "index_embeddings": {}
  }
}

ALLOW ONLY THIS TOOL → Instant setup, no code required.

The button opens the PolicyLayer dashboard: create your workspace, connect Enhanced Knowledge Graph Memory Server, apply this rule, and every index_embeddings call is checked against it from then on.

FAQ

Questions about index_embeddings

What does the index_embeddings tool do? +

Index all entities for semantic search. Call this after adding entities to enable semantic search. Requires embedding provider. It is categorised as a Read tool in the Enhanced Knowledge Graph Memory Server MCP Server, which means it retrieves data without modifying state.

How do I enforce a policy on index_embeddings? +

Register the Enhanced Knowledge Graph Memory Server MCP server in PolicyLayer and add a rule for index_embeddings: 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 Enhanced Knowledge Graph Memory Server. Nothing to install.

What risk level is index_embeddings? +

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

Can I rate-limit index_embeddings? +

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

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

index_embeddings is provided by the Enhanced Knowledge Graph Memory Server MCP server (danielsimonjr/memory-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

KEEP EXPLORING

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