by disler · MCP Server · ★ 145
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MCP From Zero: Quick Data Purpose: Learn to build Powerful Model Context Protocol (MCP) servers by scaling tools into reusable agentic workflows (ADWs aka Prompts w/tools). Quick-Data Quick-Data is a MCP server that gives your agent arbitrary data analysis on .json and .csv files. We use quick-data as a concrete use case to experiment with the MCP Server elements specifically: Prompts Tools Resources. See quick-data-mcp for details on the MCP server Leading Questions We experiment with three leading questions: How can we MAXIMIZE the value of custom built MCP servers by using tools, resources, and prompts TOGETHER? What's the BEST codebase architecture for building MCP servers? Can we build an agentic workflow (prompt w/tools) that can be used to rapidly build MCP servers? Understanding MCP Components MCP servers have three main building blocks that extend what AI models can do: Tools What: Functions that AI models can call to perform actions. When to use: When you want the AI to DO something at a low to mid atomic level based on your domain specific use cases. Example: #
| Stars | 145 |
| Forks | 30 |
| Language | Python |
| Category | MCP Server |
| Quality Score | 65.1281666502935/100 |
| Open Issues | 3 |
| Last Updated | 2025-06-01 |
| Created | 2025-06-01 |
| Platforms | claude-code, mcp, python |
| Est. Tokens | ~67k |
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quick-data-mcp is Prompt focused MCP Server for .json and .csv agentic data analytics for Claude Code. It is categorized as a MCP Server with 145 GitHub stars.
quick-data-mcp is primarily written in Python.
You can find installation instructions and usage details in the quick-data-mcp GitHub repository at github.com/disler/quick-data-mcp. The project has 145 stars and 30 forks, indicating an active community.