MCP Anthropic Server (mcp-anthropic)

An MCP (Model Context Protocol) server providing tools to interact with Anthropic's experimental prompt engineering APIs.

Features

Provides the following tools:

• generate_prompt: Generates a prompt based on a task description.
• improve_prompt: Improves an existing prompt based on feedback.
• templatize_prompt: Converts a concrete prompt example into a reusable template.

Setup

1. Clone the repository (if applicable)
2. Navigate to the project directory:

   cd mcp-anthropic
   

3. Install dependencies:

   npm install
   

4. Configure API Key:
   • Create a .env file in the project root (./mcp-anthropic/.env).
   • Add your Anthropic API key to the .env file:

     ANTHROPIC_KEY=your_anthropic_api_key_here
     

   • Ensure this file is not committed to version control (it should be covered by .gitignore).
   • Note for LibreChat Integration: For specific instructions on setting up and running this server as a child process within LibreChat (including API key handling), please refer to the documentation.md file.

Running the Server

1. Build the TypeScript code:

   npm run build
   

2. Start the server:

   npm start
   

   The server will start and listen for MCP connections. You should see output indicating the server has started and which tools are registered.

Tools Documentation

generate_prompt

Generates a prompt based on a task description.

Input Schema:

{
  "type": "object",
  "properties": {
    "task": {
      "type": "string",
      "description": "A description of the task the prompt should be designed for (e.g., \"a chef for a meal prep planning service\")."
    },
    "target_model": {
      "type": "string",
      "description": "The target Anthropic model identifier (e.g., \"claude-3-opus-20240229\")."
    }
  },
  "required": ["task", "target_model"]
}

improve_prompt

Improves an existing prompt based on feedback.

Input Schema:

{
  "type": "object",
  "properties": {
    "messages": {
      "type": "array",
      "items": {
        "type": "object",
        "properties": {
          "role": { "type": "string", "description": "Role (e.g., 'user', 'assistant')." },
          "content": {
            "type": "array",
            "items": {
              "type": "object",
              "properties": {
                "type": { "type": "string", "description": "Content type (e.g., 'text')." },
                "text": { "type": "string", "description": "Text content." }
              },
              "required": ["type", "text"]
            },
            "description": "Content blocks."
          }
        },
        "required": ["role", "content"]
      },
      "description": "The sequence of messages representing the prompt conversation."
    },
    "system": {
      "type": "string",
      "description": "(Optional) A system prompt to guide the model."
    },
    "feedback": {
      "type": "string",
      "description": "Specific feedback on how to improve the prompt (e.g., \"Make it more detailed\")."
    },
    "target_model": {
      "type": "string",
      "description": "The target Anthropic model identifier (e.g., \"claude-3-opus-20240229\")."
    }
  },
  "required": ["messages", "feedback", "target_model"]
}

templatize_prompt

Converts a concrete prompt example into a reusable template.

Input Schema:

{
  "type": "object",
  "properties": {
    "messages": {
      "type": "array",
      "items": {
        "type": "object",
        "properties": {
          "role": { "type": "string", "description": "Role (e.g., 'user', 'assistant')." },
          "content": {
            "type": "array",
            "items": {
              "type": "object",
              "properties": {
                "type": { "type": "string", "description": "Content type (e.g., 'text')." },
                "text": { "type": "string", "description": "Text content." }
              },
              "required": ["type", "text"]
            },
            "description": "Content blocks."
          }
        },
        "required": ["role", "content"]
      },
      "description": "The sequence of messages representing the prompt conversation example."
    },
    "system": {
      "type": "string",
      "description": "(Optional) A system prompt associated with the example."
    }
  },
  "required": ["messages"]
}