MCP

MCP means Model Context Protocol. It is a standard way for AI applications to connect models to tools, files, databases, and external systems.

Simple idea: MCP gives AI a clean way to use tools.

Why It Matters

LLMs become more useful when they can access context and take actions:

Read files.
Search notes.
Query databases.
Open tickets.
Call APIs.
Use internal tools.

MCP makes these connections more reusable and organized.

How It Works

An MCP server exposes tools or resources.
An AI client connects to the MCP server.
The model decides when a tool is useful.
The client calls the tool.
The result goes back into the model context.

Example

AI assistant
  -> MCP server
  -> Obsidian notes / database / API
  -> result returned to assistant

Common MCP Tools

Tool type	Example
File tools	Read and write documents
Note tools	Search Obsidian vault
Database tools	Query customer or product data
API tools	Call internal services
Browser tools	Fetch web pages
Ticket tools	Create Jira or GitHub issues

Security Questions

What can the tool read?
What can the tool write?
Can it access private data?
Does it need approval before actions?
Are tool calls logged?
Can permissions be limited per user?

CookieYes Ideas

MCP server for privacy-law notes.
MCP server for cookie scanner results.
MCP server for customer support tickets.
MCP server for consent configuration review.

Mozilor Ideas

MCP server for WebYes accessibility scans.
MCP server for WooCommerce agent actions.
MCP server for product documentation.
MCP server for AI governance logs.