Provides comprehensive instructions and setup guidance for starting to work with models from Azure AI Foundry and Azure AI Foundry Labs. This function is crucial to call whenever a user begins talking about or expressing an interest in working with Foundry models. It provides the essential protot...
How to control get_prototyping_instructions_for_github_and_labs ↓
AI agents call get_prototyping_instructions_for_github_and_labs to retrieve information from Azure AI Agent Service MCP Server without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool retrieves and delivers instructional documentation for Azure AI Foundry setup and usage. It has no side effects, does not modify data, execute code, delete resources, or move money. It is purely informational, making it a Read category tool with low severity.
From the tool's definition Tool provides 'comprehensive instructions and setup guidance' and 'prototyping instructions that include setup, configuration'.
Documented attack patterns abuse exactly the kind of access get_prototyping_instructions_for_github_and_labs 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 get_prototyping_instructions_for_github_and_labs:
{
"version": "1",
"default": "deny",
"tools": {
"get_prototyping_instructions_for_github_and_labs": {}
}
}get_prototyping_instructions_for_github_and_labs is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.
Free to start. No card required.
Provides comprehensive instructions and setup guidance for starting to work with models from Azure AI Foundry and Azure AI Foundry Labs. This function is crucial to call whenever a user begins talking about or expressing an interest in working with Foundry models. It provides the essential prototyping instructions that include setup, configuration, and the first steps in querying and utilizing the models. It should always be invoked before any other interactions with the models to ensure that the user has the necessary context and knowledge to proceed effectively. The instructions include: - Required setup for working with Foundry models. - Details about how to configure the environment. - How to query the models. - Best practices for using Foundry models in prototyping. Parameters: ctx (Context): The context of the current session, which may include session-specific information and metadata that can be used to customize the returned instructions. Returns: str: A detailed set of instructions to guide the user in setting up and using Foundry models, including steps on how to get started with queries and the prototyping process. Usage: Call this function at the beginning of any interaction involving Foundry models to provide the user with the necessary setup information and best practices. This ensures that the user can begin their work with all the foundational knowledge and tools needed. Notes: - This function should be the first step before any interaction with the Foundry models to ensure proper setup and understanding. - It is essential to invoke this function as it provides the groundwork for a successful prototyping experience with Foundry models. Importance: The function is critical for preparing the user to effectively use the Azure AI Foundry models, ensuring they have the proper guidance on how to interact with them from the very beginning. It is categorised as a Read tool in the Azure AI Agent Service MCP Server MCP Server, which means it retrieves data without modifying state.
Register the Azure AI Agent Service MCP Server MCP server in PolicyLayer and add a rule for get_prototyping_instructions_for_github_and_labs: 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.
get_prototyping_instructions_for_github_and_labs 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_prototyping_instructions_for_github_and_labs 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_prototyping_instructions_for_github_and_labs. 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_prototyping_instructions_for_github_and_labs 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.