perception_embed

[Sub-phase 4.2 — NOT YET IMPLEMENTED] Will generate Clay v1.5 embeddings.

SERVERMcp Agentcore SOURCEhttps://packagesmcp-perception-production.up.railway.app/mcp

Low RISK CLASS

Category Other

Parameters 11 required

Recommended Rate-limitedsee the rule below

Registry record Grade D, identity unverified Pull the record →

This record as markdown: /tools/com-geiant-mcp-agentcore/perception-embed.md

WHAT IT DOES

What perception_embed does on Mcp Agentcore

AI agents call perception_embed as a supporting operation in Mcp Agentcore workflows.

Parameter	Type	Required	Description
`tile_id`	string	Yes	tile_id from perception_fetch_tile result

Parameters from the server's own tool schema.

RISK

Why perception_embed is rated Low

The tool is explicitly marked as not yet implemented, meaning it performs no actual operations. When implemented, generating embeddings would likely be a Read or Execute operation (processing data to produce vector representations), but as it does nothing currently, 'Other' is most appropriate. Confidence is reduced due to the uninformative stub description.

From the tool's definition [Sub-phase 4.2 — NOT YET IMPLEMENTED] Will generate Clay v1.5 embeddings.

Attacks that exploit this kind of access

RECOMMENDED RULE

The rule that runs perception_embed safely

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

perception_embed Rate-limited

perception_embed gets a rate cap, and everything else on the server is denied unless you say otherwise.

View as policy code

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "perception_embed": {
      "limits": [
        {
          "counter": "perception_embed_rate",
          "window": "minute",
          "max": 60,
          "scope": "grant"
        }
      ]
    }
  }
}

SET A RULE FOR THIS TOOL → Instant setup, no code required.

The button opens the PolicyLayer dashboard: create your workspace, connect Mcp Agentcore, apply this rule, and every perception_embed call is checked against it from then on.

FAQ

Questions about perception_embed

What does the perception_embed tool do? +

[Sub-phase 4.2 — NOT YET IMPLEMENTED] Will generate Clay v1.5 embeddings. It is categorised as a Other tool in the Mcp Agentcore MCP Server, which means it performs auxiliary operations.

What parameters does perception_embed accept? +

perception_embed accepts 1 parameter: tile_id. Required: tile_id. The full parameter table on this page comes from the server's own tool schema.

How do I enforce a policy on perception_embed? +

Register the Mcp Agentcore MCP server in PolicyLayer and add a rule for perception_embed: 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 Mcp Agentcore. Nothing to install.

What risk level is perception_embed? +

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

Can I rate-limit perception_embed? +

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

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

perception_embed is provided by the Mcp Agentcore MCP server (https://packagesmcp-perception-production.up.railway.app/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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