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jankowtf

MCP Server Template for Cursor IDE

by jankowtf

apply_prompt_proceed

Generate structured prompts to proceed with tasks or projects in Cursor IDE, integrating specific instructions and versioned templates for efficient task management.

Instructions

Provides a prompt template for proceeding with a task or project

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
specific_instructionsNoOptional specific instructions to include in the prompt
taskYesA description of the task or project to proceed with
versionNoThe version of the prompt template to use (e.g., '1.0.0', '1.1.0', or 'latest')

Implementation Reference

  • The core execution logic for the apply_prompt_proceed tool. Renders a prompt template named 'proceed' using the provided task, specific_instructions, and version, then returns it as a TextContent object.
    async def apply_prompt_proceed( task: str, specific_instructions: str = "", version: str = "latest", ) -> list[types.TextContent]: """ Provides a prompt template for proceeding with a task or project. Args: task: A description of the task or project to proceed with. specific_instructions: Optional specific instructions to include in the prompt. version: The version of the prompt template to use. Defaults to "latest". Returns: A list containing a TextContent object with the prompt. """ # Render the prompt template with the task description and specific instructions response_text = render_prompt_template( "proceed", version_str=version, task=task, specific_instructions=specific_instructions, ) return [types.TextContent(type="text", text=response_text)]
  • The JSON schema defining the input parameters for the apply_prompt_proceed tool: required 'task' (string), optional 'specific_instructions' and 'version' (strings).
    inputSchema={ "type": "object", "required": ["task"], "properties": { "task": { "type": "string", "description": "A description of the task or project to proceed with", }, "specific_instructions": { "type": "string", "description": "Optional specific instructions to include in the prompt", }, "version": { "type": "string", "description": "The version of the prompt template to use (e.g., '1.0.0', '1.1.0', or 'latest')", }, }, },
  • The tool registration in the list_tools() decorator, which exposes the apply_prompt_proceed tool with its name, description, and input schema.
    types.Tool( name="apply_prompt_proceed", description="Provides a prompt template for proceeding with a task or project", inputSchema={ "type": "object", "required": ["task"], "properties": { "task": { "type": "string", "description": "A description of the task or project to proceed with", }, "specific_instructions": { "type": "string", "description": "Optional specific instructions to include in the prompt", }, "version": { "type": "string", "description": "The version of the prompt template to use (e.g., '1.0.0', '1.1.0', or 'latest')", }, }, }, ),
  • The dispatch logic in the generic call_tool handler that validates inputs and invokes the specific apply_prompt_proceed function.
    elif name == "apply_prompt_proceed": if "task" not in arguments: return [ types.TextContent( type="text", text="Error: Missing required argument 'task'" ) ] version = arguments.get("version", "latest") specific_instructions = arguments.get("specific_instructions", "") return await apply_prompt_proceed( arguments["task"], specific_instructions=specific_instructions, version=version, )

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