Retrieves the schema for a specific index
AI agents call retrieve_index_schema to retrieve information from Azure Ai Search Python Preview without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool retrieves information about an index structure without side effects. It performs a query operation to fetch schema details, which is characteristic of Read category tools. The low severity reflects minimal blast radius—schema information alone cannot cause harm unless it exposes sensitive structural details that inform further attacks, but the immediate impact is informational only.
From the tool's definition Tool name 'retrieve_index_schema' and description 'Retrieves the schema for a specific index' indicate a read-only operation that queries and returns schema metadata without modifying any data.
Attacks that exploit this kind of access
Retrieves the schema for a specific index. It is categorised as a Read tool in the Azure Ai Search Python Preview MCP Server, which means it retrieves data without modifying state.
Register the Azure Ai Search Python Preview MCP server in PolicyLayer and add a rule for retrieve_index_schema: 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.
retrieve_index_schema is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the retrieve_index_schema 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.
Set action: deny in the PolicyLayer policy for retrieve_index_schema. 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.
retrieve_index_schema 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.
Every MCP server has a record like this.
Type a name, get the same breakdown: verified identity, auth posture, risk grade, capabilities, recommended policy.
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