Mcp

AI coding tools are powerful, but they are blind. They can read your code, but they cannot see your GitHub issues. They can write database queries, but they do not know your schema. They can suggest fixes, but they cannot check your CI pipeline. MCP changes that. The Model Context Protocol connects your AI tools to external systems — databases, GitHub, file systems, APIs, and anything else you build a server for. Think of it as USB-C for AI. One standard protocol, many connections. ...

You have probably seen “MCP” everywhere lately. Every AI tool seems to support it now. But what is it actually? The problem before MCP Imagine you have 10 AI tools and 20 data sources. Databases, APIs, file systems, Slack, GitHub. Each AI tool needed its own custom integration with each data source. That is 200 different integrations to build and maintain. Developers called this the N×M problem. What MCP does Model Context Protocol is a standard. Like USB-C, but for AI. ...

Every AI coding tool has the same problem: it can read your code, but it can’t access your database. It can’t check your Jira tickets. It can’t read your Slack messages. It can’t query your production logs. Until now. MCP (Model Context Protocol) is a new standard that lets AI tools connect to anything — databases, APIs, file systems, project management tools, and more. It is like a USB-C port for AI. One standard connection that works with everything. ...