MCP-Server---Datasaur
The project is a beginner-friendly guide to setting up a Model Context Protocol (MCP) server using the Datasaur Sandbox. It acts as a bridge for applications to communicate with AI models via Datasaur's API endpoints. Key features include data processing, AI model access, and tool development.
MCP Server with Datasaur Sandbox
A comprehensive guide for beginners to set up and use a Model Context Protocol (MCP) server with Datasaur Sandbox.
Introduction
What is MCP?
Model Context Protocol (MCP) is a standardized way for applications to communicate with AI models.
What is a Datasaur Sandbox?
Datasaur Sandbox provides managed API access to various AI models, acting as a bridge between your applications and Datasaur's API endpoints.
Prerequisites
- Python 3.8+
- A Datasaur account with API access
- Basic knowledge of command-line operations
Installation
- Clone or create the project directory.
- Set up a virtual environment.
- Install dependencies.
- Create essential files.
Configuration
Configuration involves setting up a .env file for API keys and service URLs.
Running Your MCP Server
Instructions are provided for running the MCP server both directly and with Claude Desktop.
Using Your MCP Server
Your MCP server acts as a bridge to implement data processing tools, AI model access, and helper tools.
Troubleshooting
Solutions for common errors like API configuration issues are provided.
Extending Functionality
Details on how to add new models, customize response processing, and enhance authentication.
Resources
Links to relevant documentation and resources.