get_prompt
Retrieve rendered prompt messages from the MCP Test MCP server by specifying a prompt name and required arguments.
Instructions
Get a rendered prompt from the connected MCP server.
Retrieves a prompt by name with the provided arguments and returns the rendered prompt messages.
Returns: Dictionary with rendered prompt including: - success: True if prompt was retrieved successfully - prompt: Object with name, description, and rendered messages - metadata: Request timing and server information
Raises: Returns error dict for various failure scenarios: - not_connected: No active connection - prompt_not_found: Prompt doesn't exist on server - invalid_arguments: Arguments don't match prompt schema - execution_error: Prompt retrieval failed
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes | Name of the prompt to retrieve | |
| arguments | Yes | Dictionary of arguments to pass to the prompt |
Implementation Reference
- The core handler function for the 'get_prompt' tool. Decorated with @mcp.tool for automatic registration. It verifies connection, calls the connected client's get_prompt, processes result messages (handling various content types), increments prompts_executed stat, provides user feedback via ctx.info/error, and returns detailed success/error response with metadata.
@mcp.tool async def get_prompt( name: Annotated[str, "Name of the prompt to retrieve"], arguments: Annotated[dict[str, Any], "Dictionary of arguments to pass to the prompt"], ctx: Context ) -> dict[str, Any]: """Get a rendered prompt from the connected MCP server. Retrieves a prompt by name with the provided arguments and returns the rendered prompt messages. Returns: Dictionary with rendered prompt including: - success: True if prompt was retrieved successfully - prompt: Object with name, description, and rendered messages - metadata: Request timing and server information Raises: Returns error dict for various failure scenarios: - not_connected: No active connection - prompt_not_found: Prompt doesn't exist on server - invalid_arguments: Arguments don't match prompt schema - execution_error: Prompt retrieval failed """ start_time = time.perf_counter() try: # Verify connection exists client, state = ConnectionManager.require_connection() # User-facing progress update await ctx.info(f"Getting prompt '{name}' with arguments") # Detailed technical log logger.info( f"Getting prompt '{name}' with arguments", extra={"prompt_name": name, "arguments": arguments}, ) # Get the prompt prompt_start = time.perf_counter() result = await client.get_prompt(name, arguments) prompt_elapsed_ms = (time.perf_counter() - prompt_start) * 1000 # Increment statistics ConnectionManager.increment_stat("prompts_executed") total_elapsed_ms = (time.perf_counter() - start_time) * 1000 # Extract prompt messages messages = [] if hasattr(result, "messages") and result.messages: for message in result.messages: message_dict: dict[str, Any] = { "role": message.role, } # Handle different content types # Content can be: TextContent, ImageContent, AudioContent, ResourceLink, EmbeddedResource if hasattr(message, "content"): content = message.content if hasattr(content, "type"): # Structured content with type discriminator content_dict: dict[str, Any] = { "type": content.type, } # Handle type-specific fields if content.type == "text" and hasattr(content, "text"): content_dict["text"] = content.text elif content.type == "image" and hasattr(content, "data"): content_dict["data"] = content.data if hasattr(content, "mimeType"): content_dict["mimeType"] = content.mimeType elif content.type == "audio" and hasattr(content, "data"): content_dict["data"] = content.data if hasattr(content, "mimeType"): content_dict["mimeType"] = content.mimeType elif content.type == "resource": # ResourceLink or EmbeddedResource if hasattr(content, "uri"): content_dict["uri"] = content.uri if hasattr(content, "resource"): content_dict["resource"] = content.resource message_dict["content"] = content_dict else: # Fallback for simple/unknown content types message_dict["content"] = {"type": "text", "text": str(content)} messages.append(message_dict) prompt_info = { "name": name, "description": result.description if hasattr(result, "description") and result.description else "", "messages": messages, } # User-facing success update await ctx.info(f"Prompt '{name}' retrieved successfully with {len(messages)} messages") # Detailed technical log logger.info( f"Prompt '{name}' retrieved successfully", extra={ "prompt_name": name, "message_count": len(messages), "duration_ms": prompt_elapsed_ms, }, ) return { "success": True, "prompt": prompt_info, "metadata": { "request_time_ms": round(total_elapsed_ms, 2), "server_url": state.server_url, "connection_statistics": state.statistics, }, } except ConnectionError as e: elapsed_ms = (time.perf_counter() - start_time) * 1000 # User-facing error update await ctx.error(f"Not connected when getting prompt '{name}': {str(e)}") # Detailed technical log logger.error( f"Not connected when getting prompt '{name}': {str(e)}", extra={"prompt_name": name, "duration_ms": elapsed_ms}, ) return { "success": False, "error": { "error_type": "not_connected", "message": str(e), "details": {"prompt_name": name}, "suggestion": "Use connect_to_server() to establish a connection first", }, "prompt": None, "metadata": { "request_time_ms": round(elapsed_ms, 2), }, } except Exception as e: elapsed_ms = (time.perf_counter() - start_time) * 1000 # Determine error type based on exception message error_type = "execution_error" suggestion = "Check the prompt name and arguments, then retry" error_msg = str(e).lower() if "not found" in error_msg or "unknown prompt" in error_msg or "no prompt" in error_msg: error_type = "prompt_not_found" suggestion = f"Prompt '{name}' does not exist on the server. Use list_prompts() to see available prompts" elif "argument" in error_msg or "parameter" in error_msg or "validation" in error_msg or "required" in error_msg: error_type = "invalid_arguments" suggestion = f"Arguments do not match the prompt schema. Use list_prompts() to see the correct schema for '{name}'" # User-facing error update await ctx.error(f"Failed to get prompt '{name}': {str(e)}") # Detailed technical log logger.error( f"Failed to get prompt '{name}': {str(e)}", extra={ "prompt_name": name, "arguments": arguments, "error_type": error_type, "duration_ms": elapsed_ms, }, ) # Increment error counter ConnectionManager.increment_stat("errors") return { "success": False, "error": { "error_type": error_type, "message": f"Failed to get prompt '{name}': {str(e)}", "details": { "prompt_name": name, "arguments": arguments, "exception_type": type(e).__name__, }, "suggestion": suggestion, }, "prompt": None, "metadata": { "request_time_ms": round(elapsed_ms, 2), }, } - node-wrapper/python-src/src/mcp_test_mcp/server.py:98-98 (registration)Import statement in the main server module that loads the prompts module, triggering the execution of @mcp.tool decorators and thus registering the get_prompt tool on the shared FastMCP instance.
from .tools import connection, tools, resources, prompts, llm - The shared FastMCP server instance 'mcp' to which all tools are registered via @mcp.tool decorators used in tool modules like prompts.py.
mcp = FastMCP(name="mcp-test-mcp")