Sample Routing Prompt for MS Learn MCP Tool

The following provides a complete example prompt for using the MCP Client Tool to target the Microsoft Learn MCP server.

Prompt Contents

MCPClientTool

The MCP Client Tool provides a simplified interface for invoking MCP Server tools where agents can delegate tool discovery, selection, and execution to the tool itself. The tool is configured to work against a specific MCP server as described below.

MCP Server: This MCPClient tool has been configured as client of the Microsoft Learn MCP Server.

MCP Server Purpose: The Microsoft Learn MCP Server is best for querying Microsoft Documentation. It provides tools that allow you to search through and fetch Microsoft's latest official documentation and code samples, and that information might be more detailed or newer than what's in your training data set. When handling questions around how to work with native Microsoft technologies, such as Azure, M365, C#, F#, ASP.NET Core, Microsoft.Extensions, NuGet, Entity Framework, the dotnet runtime - please use these tools for research purposes when dealing with specific / narrowly defined questions that may occur.

Primary Approach: Intelligent Execute

Use intelligent_execute for most scenarios - this allows the agent to provide a natural language prompt and let the MCP Client Tool handle:

Discovering available tools on the MCP server
Selecting appropriate tools based on the user's request
Executing the tools with proper arguments
Synthesizing results into a coherent response

Example Usage

{
  "operation": "intelligent_execute",
  "arguments": {
    "prompt": "Search for information about Azure authentication best practices"
  }
}

For Microsoft Learn MCP server, this would automatically:

Discover the microsoft_docs_search tool
Execute the search with appropriate query parameters
Synthesize the results into a comprehensive response

More Examples

{
  "operation": "intelligent_execute",
  "arguments": {
    "prompt": "Find code samples for ASP.NET Core web API development"
  }
}

{
  "operation": "intelligent_execute",
  "arguments": {
    "prompt": "Get the latest documentation on Azure Functions deployment"
  }
}

Manual Approach (Advanced)

When you need precise control over MCP operations, use the manual approach:

Discover Available Tools

{
  "operation": "list_tools",
  "arguments": {}
}

Call Specific Tools

{
  "operation": "call_tool",
  "arguments": {
    "name": "tool_name",
    "arguments": {
      "param1": "value1",
      "param2": "value2"
    },
    "read_timeout_seconds": 30
  },
  "response_format": "json"
}

Other Operations

{
  "operation": "list_resources",
  "arguments": {}
}

{
  "operation": "read_resource",
  "arguments": {
    "uri": "resource://path/to/resource"
  },
  "read_timeout_seconds": 60
}

System Guidance for the Agent

Prefer intelligent_execute for most user requests - it handles complexity automatically
The MCP Client Tool requires top-level fields: operation and arguments
For intelligent_execute, simply provide a clear, descriptive prompt in the arguments.prompt field
Use manual operations only when you need specific control or when intelligent_execute doesn't meet your needs
Use response_format: "json" and set reasonable timeouts for long operations
Token tracking: The tool automatically tracks LLM token usage for intelligent_execute operations

Configuration Requirements

For intelligent_execute to work properly, ensure the tool is configured with:

Main Model Resource: An LLM configured as main_model resource
Main Prompt Resource: An orchestration prompt configured as main_prompt resource

Answering Behavior

Default to intelligent_execute for user queries that involve MCP server interactions
Provide clear, descriptive prompts that specify what information the user is seeking
Let the tool handle tool discovery and execution - don't manually discover tools unless necessary
Present the synthesized results in a user-friendly format
Include relevant metadata and links returned by the MCP server when appropriate

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