Return the total number of documents in the index
AI agents call get_document_count 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 performs a read-only retrieval of document count statistics from a search index. It has no side effects, does not execute code or commands, does not modify data, and does not involve financial operations. The blast radius of misuse is minimal—an agent could only obtain count information about indexed data, which is non-sensitive metadata. Classified as Read with low severity.
From the tool's definition Tool name 'get_document_count' and description 'Return the total number of documents in the index' indicate a pure query operation that retrieves aggregated metadata without modifying data.
Attacks that exploit this kind of access
Return the total number of documents in the 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 get_document_count: 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.
get_document_count 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 get_document_count 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 get_document_count. 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.
get_document_count 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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