Send a query to the default configured Azure AI Agent. Parameters: - query: Text query to send to the default agent Returns a dict with the agent's response and thread/run IDs for potential evaluation
AI agents invoke query_default_agent to trigger actions in Azure AI Agent Service MCP Server. 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.
This tool triggers an external operation by sending a query to an Azure AI Agent, which may invoke models, search tools, Bing grounding, or other backend operations. It is not a simple read — it initiates a run on a remote agent system whose effects depend on the query content. This maps to Execute.
From the tool's definition Send a query to the default configured Azure AI Agent
Documented attack patterns abuse exactly the kind of access query_default_agent gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Azure AI Agent Service MCP Server, and nothing reaches the server without passing your rules. This is the rule we recommend for query_default_agent:
{
"version": "1",
"default": "deny",
"tools": {
"query_default_agent": {
"limits": [
{
"counter": "query_default_agent_rate",
"window": "minute",
"max": 10,
"scope": "grant"
}
]
}
}
}query_default_agent 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.
Free to start. No card required.
Send a query to the default configured Azure AI Agent. Parameters: - query: Text query to send to the default agent Returns a dict with the agent's response and thread/run IDs for potential evaluation. It is categorised as a Execute tool in the Azure AI Agent Service MCP Server MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Azure AI Agent Service MCP Server MCP server in PolicyLayer and add a rule for query_default_agent: 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 MCP Server. Nothing to install.
query_default_agent is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.
Yes. Add a rate_limit block to the query_default_agent 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 query_default_agent. 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.
query_default_agent is provided by the Azure AI Agent Service MCP Server MCP server (microsoft-foundry/mcp-foundry). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Azure AI Agent Service MCP Server, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
Free to start. No card required.
28 Azure AI Agent Service MCP Server tools catalogued and risk-classified — across an index of 43,000+ MCP servers.