How to represent function/tool metadata inside MCP?

 

Step 1: Understand MCP Components

 

To effectively represent function/tool metadata within the MCP framework, you first need to understand the common components of MCP:

• System Instructions:

  Define the overall role of the model. Example: "You are a helpful assistant specialized in finance."

• User Profile:

  Includes user details such as name, preferences, and goals.

• Document Context:

  Encompasses the knowledge base and any recent uploads relevant to the task.

• Active Tasks / Goals:

  Lists current objectives or to-dos.

• Tool Access:

  Specifies which functions or tools the model can utilize, such as web scraping, database access, etc.

• Rules / Constraints:

  Sets boundaries for the model, such as "never suggest medical diagnoses."

 

Step 2: Structuring Tool Metadata

 

When representing tool metadata, consider the following elements:

• Tool Name:

  The name of the function or tool.

• Tool Description:

  A brief explanation of what the tool does.

• Access Methods:

  How the tool can be accessed or called.

• Input Requirements:

  The necessary data needed for the tool to function.

• Output Details:

  What the tool returns after execution.

 

Step 3: Code Representation

 

Here's how you might structure this metadata using JSON within a MCP-compliant system:

{
  "tools": [
    {
      "tool_name": "WebScraper",
      "tool_description": "A tool to scrape web data based on given parameters.",
      "access_methods": ["API", "Command-line"],
      "input_requirements": {
        "url": "The web URL to scrape data from",
        "data_type": "Type of data needed (e.g., text, images)"
      },
      "output_details": {
        "format": "JSON",
        "schema": {
          "title": "string",
          "content": "string",
          "images": ["string"]
        }
      }
    }
  ]
}

 

Step 4: Define Tool Access Context within MCP

 

Integrating tool metadata with MCP involves defining the tool within the Tool Access component of MCP. This standardization ensures predictability and facilitates modular usage:

{
  "mcp_version": "1.0",
  "system_instructions": "You are a versatile assistant capable of using various tools.",
  "tool_access": {
    "WebScraper": {
      "description": "Scrapes data from a provided URL",
      "api_key": "Optional API key for access"
    }
  },
  "rules_constraints": [
    "Ensure all web scraping complies with site terms of use."
  ]
}

 

Step 5: Test and Validate Metadata Integration

 

Finally, run tests to validate that the tool metadata is functioning correctly within the MCP framework. This step might include:

• Ensuring that tools are accessible as defined in the Tool Access component.
• Verifying that input requirements are met before tool invocation.
• Checking output formats and data structure against Output Details.

 

By following these steps, you can effectively represent function or tool metadata within the MCP framework in the context of AI and language models, ensuring that they behave predictably and effectively across different use cases.