Prompts in the client

MCP Client and Prompt Management

Client Implementation Tasks:

• List Prompts: The client must implement a function to retrieve all defined prompts from the MCP server.
• Action: Call self. session. list_prompts.
• Return Value: result. prompts.
• Get Prompt: The client retrieves a specific prompt by name and provides necessary arguments.
• Input: Prompt name and a dictionary of arguments.
• Process: Call self. session. get_prompt(prompt_name, arguments).
• Return Value: result. messages (These messages form the conversation fed to the LLM).

Prompt Retrieval and Interpolation:

• Arguments: When retrieving a prompt, arguments (e. g. , a document ID) are passed to the prompting function.
• Interpolation: The prompt function uses these arguments (passed as keyword arguments) to dynamically insert values into the prompt template itself.
• Invocation: The prompt name acts as the command (e. g. , "format"). The user provides the required arguments (e. g. , document ID).
• Execution Flow:
• The client sends the prompt instructions + arguments to the LLM.
• The LLM processes the instruction (e. g. , "reformat").
• The LLM uses available tools (e. g. , get_document_tool) to fetch necessary data.
• The LLM responds with the final, processed output.

Conceptual Summary:

• A prompt is a defined instruction within the MCP server, designed for a specific task (e. g. , rewriting a document).
• The client requests this prompt, supplying required variables.
• The prompt function integrates these variables into the instruction before execution.

Takeaways

• The client must implement functions to list and retrieve specific prompts from the MCP server.
• A prompt is a defined instruction within the MCP server designed for a specific task.
• Arguments are passed to the prompt function and dynamically interpolated into the prompt template.
• Execution involves the client sending instructions and arguments to the LLM, which then uses available tools to generate the final output.