create_foundry_project

WHAT IT DOES

What create_foundry_project does on Azure AI Agent Service MCP Server

AI agents use create_foundry_project to create or update resources in Azure AI Agent Service MCP Server — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Azure AI Agent Service MCP Server environment.

THE RISK

Medium Risk

Why create_foundry_project needs a policy

This tool creates a new project in Azure AI Foundry, which is a reversible Write operation—projects can be deleted or modified. It does not execute code, delete data irreversibly, or move money.

From the tool's definition Tool name is 'create_foundry_project' which clearly indicates creation of a new project resource in Azure AI Foundry.

Documented attack patterns abuse exactly the kind of access create_foundry_project gives an agent:

POLICY

How to control create_foundry_project

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 create_foundry_project:

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "create_foundry_project": {
      "limits": [
        {
          "counter": "create_foundry_project_rate",
          "window": "minute",
          "max": 30,
          "scope": "grant"
        }
      ]
    }
  }
}

create_foundry_project stays usable, but capped — an agent stuck in a loop can't make hundreds of changes a minute. Everything else on the server is denied unless you say otherwise.

Create a free account and register Azure AI Agent Service MCP Server — nothing to install.
Add this policy — paste it, or build it visually.
Point your MCP client (Claude, Cursor, anything) at your gateway URL.

LIMIT THIS TOOL →

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EXPLORE

Related tools and policies

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All 28 Azure AI Agent Service MCP Server tools →

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Go deeper

The MCP Attack Database → Documented attack patterns against MCP deployments — and the policies that stop them.
Argument validation → Checking tool call arguments against schema and policy before they run.
Scoped token → Per-person credentials that grant a defined subset of servers and tools.
Rate Limiting MCP Tool Calls: A Practical Guide →
MCP Security: Why Prompt Guardrails Aren't Enough →

FAQ

Questions about create_foundry_project

What does the create_foundry_project tool do? +

create_foundry_project. It is categorised as a Write tool in the Azure AI Agent Service MCP Server MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.

How do I enforce a policy on create_foundry_project? +

Register the Azure AI Agent Service MCP Server MCP server in PolicyLayer and add a rule for create_foundry_project: 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.

What risk level is create_foundry_project? +

create_foundry_project is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.

Can I rate-limit create_foundry_project? +

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

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

create_foundry_project 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.

Enforce policy on every Azure AI Agent Service MCP Server tool call.

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.

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28 Azure AI Agent Service MCP Server tools catalogued and risk-classified — across an index of 43,000+ MCP servers.