Claude With Amazon Bedrock
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Lesson 63Claude With Amazon Bedrock

Prompts in the client

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MCP Client and Prompt Management

Client Functionality:

  • List Prompts: The client can retrieve a list of all defined prompts from the MCP server.
  • Get Prompt: The client retrieves a specific prompt by providing its name and necessary arguments.
  • The client passes the prompt name and arguments to the server session.
  • The function returns the prompt's messages, which are used to form the conversation fed to the LLM/Cloud.

Prompt Mechanics and Variables:

  • Prompt Definition: Prompts are defined within the MCP server and are designed to perform specific tasks (e. g. , document rewriting).
  • Arguments/Variables: When requesting a prompt, arguments (e. g. , a document ID) are provided.
  • Interpolation: These arguments are passed to the prompting function as keyword arguments and are then used to dynamically insert values into the prompt itself.

Workflow Example (Document Reformatting):

  • Invocation: A user invokes a prompt (e. g. , format) via the CLI, providing necessary inputs (e. g. , a document ID).
  • Instruction Delivery: The prompt, which contains the user's instructions and the document ID, is sent to the LLM/Cloud.
  • Tool Usage: The LLM receives the instructions and the ID, and uses a designated tool (e. g. , get document tool) to fetch the document's content.
  • Output: The LLM processes the fetched content according to the prompt's instructions and returns the final, reformatted output.

Conceptual Recap:

  • The process begins by writing and evaluating a prompt relevant to the server's purpose.
  • The prompt is defined within the MCP server.
  • The client requests the prompt, supplying arguments as keyword inputs.
  • The prompt function utilizes these keyword arguments to customize the final prompt.

Takeaways

  • MCP Clients retrieve and execute prompts that are defined and managed within the MCP Server.
  • Arguments are passed by the client and used for dynamic interpolation, customizing the prompt's content.
  • The LLM processes the final prompt by utilizing designated tools (e. g. , fetching document content) based on the instructions.
  • The workflow involves the client supplying keyword inputs to the server-side prompt function for execution.
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