create_indexer · Azure Ai Search Python Preview MCP

WHAT IT DOES

What create_indexer does on Azure Ai Search Python Preview

AI agents use create_indexer to create or update resources in Azure Ai Search Python Preview — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Azure Ai Search Python Preview environment.

WHY IT NEEDS A POLICY

Why create_indexer needs a policy

Creating an indexer is a reversible write operation—it creates a new search indexer configuration that can be modified or deleted later. While it does not destroy data or execute arbitrary code, it modifies the search infrastructure by adding a new indexing pipeline.

From the tool's definition Tool name 'create_indexer' and description 'Creates a new indexer' indicate creation of a new configuration object. The server description states it enables 'read and write operations on search indices, indexers, and documents via natural language.'

Attacks that exploit this kind of access

Recommended rule Ready

Verdict

create_indexer Rate-limited

create_indexer 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.

View as policy code

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "create_indexer": {
      "limits": [
        {
          "counter": "create_indexer_rate",
          "window": "minute",
          "max": 30,
          "scope": "grant"
        }
      ]
    }
  }
}

LIMIT THIS TOOL →

Instant setup, no code required.

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

FAQ

Questions about create_indexer

What does the create_indexer tool do? +

Creates a new indexer. It is categorised as a Write tool in the Azure Ai Search Python Preview MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.

How do I enforce a policy on create_indexer? +

Register the Azure Ai Search Python Preview MCP server in PolicyLayer and add a rule for create_indexer: 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 Azure Ai Search Python Preview. Nothing to install.

What risk level is create_indexer? +

create_indexer is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.

Can I rate-limit create_indexer? +

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

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

create_indexer is provided by the Azure Ai Search Python Preview MCP server (projectacetylcholine/mcp-server-azure-ai-search-python-preview). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.