What is MCP
By definition, MCP (Model Context Protocol) is an open-source standard for connecting AI applications to external systems.
Using MCP, AI applications like Claude or ChatGPT can connect to data sources (e.g. local files, databases), tools (e.g. search engines, calculators) and workflows (e.g. specialized prompts)—enabling them to access key information and perform tasks.
The Three Pillars of MCP
Resources: Think of these as read-only data bridges. Whether it’s a local SQLite database, a Google Drive folder, or a GitHub repo, the AI can now "see" the data it needs to provide accurate, grounded answers.
Tools: This enables the AI to do things. It could be executing a Python script, triggering a web search, or performing complex calculations through a specialized API.
Prompts: MCP allows for standardized "templates" or workflows. This ensures the AI follows specific, high-quality logic consistently across different platforms.
What people really need for MCP
I wrote the markdown formatter (AI-Answer-Copier) months ago. In order to build a bridge between AI answers to saved document, I integrated functions of markdown conversion to multiple format into this MCP.
Here is one of the published version of markdown formatter statistics.
For this sites only, we get at least 6000 usage in the last 30 days, while this is not high. But I can say, this MCP at least serve some part of purposes of what people want.
For HTML online version, see: AI-answer-copier
As you can see, most users use markdown to DOCX. The usage is higher than others. It means most users still prefer to use DOCX for convenient purposes.
It is not hard to understand, markdown is exclusive to computer related workers like developers or AI engineers. Managers still like to use DOCX for their works and modify it at their wish.
Which part of this tool is different to claude chatbox?
Some people might curious, claude.ai already has docx output if you ask them in the chatbox. Why a duplicated tool is needed.
First, claude use python or HTML to generate DOCX, while it is good for one run output of files. It did not, however, serve the purpose for multi run if user want to export every part of their chat into DOCX.
Second, user may want to export to other format, like to PDF, without their manual conversion using MSOffice offline. This is what this tool build for.
How could you build a MCP that people likes?
Build a bridge for what people need
There are still many gaps between what user want between AI output. For example, corporations might deploy LLM with agent to replace human customer services.
One problem existing in here is, AI don't have authority to touch IT system which human customer services can have access to, and AI usually hallucinate, answer different than what people want.
The most important question is, most of client feedback is not about generalized ideas but focusing on specific problems. Like:
"My phone can't receive a verification SMS for your app"
,which can only be solved by a senior engineer.
What is your idea on AI customer service to solve this kind of problem?