cdli-mcp-server

cdli-mcp-server

3.3

The Cuneiform Digital Library Initiative (CDLI) MCP Server is designed to facilitate the management and processing of cuneiform data using the Model Context Protocol (MCP).

The CDLI MCP Server is a specialized server that supports the management and processing of cuneiform data, which is an ancient writing system used in the Near East. The server leverages the Model Context Protocol (MCP) to provide a structured and efficient way to handle the complex data associated with cuneiform tablets. This server is part of the broader Cuneiform Digital Library Initiative, which aims to digitize and make accessible the vast collections of cuneiform tablets held in museums and collections around the world. By using MCP, the server ensures that data is processed in a consistent and standardized manner, facilitating research and collaboration among scholars and institutions.

Features

  • Efficient Data Management: Provides tools for managing large datasets of cuneiform inscriptions.
  • Standardized Protocol: Utilizes MCP for consistent data processing and communication.
  • Integration with CDLI: Seamlessly integrates with the Cuneiform Digital Library Initiative's resources.
  • Scalability: Designed to handle growing datasets as more cuneiform tablets are digitized.
  • Collaboration Support: Facilitates collaboration among researchers and institutions.

Usage with Different Platforms

python

python
import mcp

# Initialize MCP server connection
server = mcp.connect('cdli-mcp-server')

# Fetch data
data = server.fetch_data('cuneiform_tablets')

# Process data
processed_data = mcp.process(data)

# Display results
print(processed_data)

java

java
import mcp.MCPClient;

public class CDLIClient {
    public static void main(String[] args) {
        MCPClient client = new MCPClient("cdli-mcp-server");
        
        // Fetch data
        String data = client.fetchData("cuneiform_tablets");
        
        // Process data
        String processedData = client.processData(data);
        
        // Display results
        System.out.println(processedData);
    }
}