indexfoundry_index_embed · IndexFoundry MCP: Risk & Policy

WHAT IT DOES

What indexfoundry_index_embed does on IndexFoundry MCP

AI agents invoke indexfoundry_index_embed to trigger actions in IndexFoundry MCP. What it does depends on the arguments the agent supplies, and its effects often reach beyond the immediate call — builds kicked off, notifications sent, workflows started.

WHY IT NEEDS A POLICY

Why indexfoundry_index_embed needs a policy

This tool triggers external operations (calling OpenAI API or local models) to generate embeddings. It executes computational processes and makes external API calls, which goes beyond simple data reads or writes. The batch processing with retry logic indicates it orchestrates external service interactions. Misuse could result in excessive API usage/costs or unintended processing of sensitive content.

From the tool's definition Generate vector embeddings for chunks using OpenAI or local models. Batch processing with retry logic and rate limiting.

Attacks that exploit this kind of access

Recommended rule Ready

Verdict

indexfoundry_index_embed Rate-limited

indexfoundry_index_embed stays usable, but rate-capped — a runaway agent can't fire it dozens of times a minute. Everything else on the server is denied unless you say otherwise.

View as policy code

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "indexfoundry_index_embed": {
      "limits": [
        {
          "counter": "indexfoundry_index_embed_rate",
          "window": "minute",
          "max": 10,
          "scope": "grant"
        }
      ]
    }
  }
}

RATE-LIMIT THIS TOOL →

Instant setup, no code required.

PolicyLayer is an MCP gateway: every tool call is checked against your rule before it reaches IndexFoundry MCP, so you can run agents against it safely.

FAQ

Questions about indexfoundry_index_embed

What does the indexfoundry_index_embed tool do? +

Generate vector embeddings for chunks using OpenAI or local models. Batch processing with retry logic and rate limiting. It is categorised as a Execute tool in the IndexFoundry MCP MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.

How do I enforce a policy on indexfoundry_index_embed? +

Register the IndexFoundry MCP server in PolicyLayer and add a rule for indexfoundry_index_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 IndexFoundry MCP. Nothing to install.

What risk level is indexfoundry_index_embed? +

indexfoundry_index_embed is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.

Can I rate-limit indexfoundry_index_embed? +

Yes. Add a rate_limit block to the indexfoundry_index_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 indexfoundry_index_embed completely? +

Set action: deny in the PolicyLayer policy for indexfoundry_index_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 indexfoundry_index_embed? +

indexfoundry_index_embed is provided by the IndexFoundry MCP server (mnehmos/mnehmos.index-foundry.mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.