Execute a dynamically generated tool from the Swagger specification. Args: tool_name: Name of the tool (operation ID) params: Parameters for the API call Returns: JSON string with the API response
AI agents invoke execute_dynamic_swagger_action 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 permits execution of arbitrary API operations from a Swagger specification with agent-controlled parameters. While not directly destructive or financial on its own, the dynamic nature and broad parameter passing means an agent could invoke delete operations, financial transactions, or other side-effecting API calls.
From the tool's definition Tool name 'execute_dynamic_swagger_action' combined with description stating it 'Execute[s] a dynamically generated tool from the Swagger specification' with arbitrary **params.
Documented attack patterns abuse exactly the kind of access execute_dynamic_swagger_action 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 execute_dynamic_swagger_action:
{
"version": "1",
"default": "deny",
"tools": {
"execute_dynamic_swagger_action": {
"limits": [
{
"counter": "execute_dynamic_swagger_action_rate",
"window": "minute",
"max": 10,
"scope": "grant"
}
]
}
}
}execute_dynamic_swagger_action 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.
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Execute a dynamically generated tool from the Swagger specification. Args: tool_name: Name of the tool (operation ID) params: Parameters for the API call Returns: JSON string with the API response. 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 execute_dynamic_swagger_action: 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.
execute_dynamic_swagger_action 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 execute_dynamic_swagger_action 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 execute_dynamic_swagger_action. 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.
execute_dynamic_swagger_action 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.