vector_search

Perform a vector similarity search on the Azure AI Search index.

SERVERAzure AI Agent Service + Azure AI Search MCP Server SOURCE0lovesakura0/mcp-server-azure-ai-agents-main

Low RISK CLASS

Category Read

Parameters 00 required

Recommended Allowedsee the rule below

Registry record Grade A, identity unverified Pull the record →

This record as markdown: /tools/0lovesakura0-mcp-server-azure-ai-agents-main/vector-search.md

WHAT IT DOES

What vector_search does on Azure AI Agent Service + Azure AI Search MCP Server

AI agents call vector_search to retrieve information from Azure AI Agent Service + Azure AI Search MCP Server without modifying anything. It is typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.

RISK

Why vector_search is rated Low

Vector search queries a pre-built index to retrieve semantically similar documents based on embedding similarity. This is a passive data retrieval operation with no side effects, no data modification, no code execution, and no financial impact. The primary risk is information disclosure if sensitive documents are indexed, but the tool itself is a standard read operation.

From the tool's definition Tool performs 'vector similarity search' on an index, returning matching documents without modifying, creating, or deleting data. The verb 'search' and description explicitly indicate read-only retrieval.

Attacks that exploit this kind of access

RECOMMENDED RULE

The rule that runs vector_search safely

PolicyLayer is an MCP gateway: it sits between your AI agents and Azure AI Agent Service + Azure AI Search MCP Server, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For vector_search, this is the rule to start with:

vector_search Allowed

vector_search is read-only, so it stays allowed. Everything else on the server is denied unless you say otherwise.

View as policy code

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "vector_search": {}
  }
}

ALLOW ONLY THIS TOOL → Instant setup, no code required.

The button opens the PolicyLayer dashboard: create your workspace, connect Azure AI Agent Service + Azure AI Search MCP Server, apply this rule, and every vector_search call is checked against it from then on.

FAQ

Questions about vector_search

What does the vector_search tool do? +

Perform a vector similarity search on the Azure AI Search index. It is categorised as a Read tool in the Azure AI Agent Service + Azure AI Search MCP Server MCP Server, which means it retrieves data without modifying state.

How do I enforce a policy on vector_search? +

Register the Azure AI Agent Service + Azure AI Search MCP Server MCP server in PolicyLayer and add a rule for vector_search: 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 Agent Service + Azure AI Search MCP Server. Nothing to install.

What risk level is vector_search? +

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

Can I rate-limit vector_search? +

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

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

vector_search is provided by the Azure AI Agent Service + Azure AI Search MCP Server MCP server (0lovesakura0/mcp-server-azure-ai-agents-main). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

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