Bifalgorithm post

Do we really need MCP when we already have APIs? Let's understand the difference between the two. An API is how two pieces of software communicate. Let's say you build an app that needs to read issues from GitHub. GitHub exposes an API. Your app sends a request to GitHub, and GitHub sends the data back. Simple, but real applications usually talk to many services. GitHub for code. Gmail for emails. Jira for tickets. Notion for documents. Your database for user data. For each service, you need integration code. Authentication, API calls, error handling, retries, and logic for understanding the response. Now let's add an LLM. The application can now understand what the user wants and decide what action should happen, but the model itself usually doesn't directly call GitHub. It says something like, get the open issues from this repository. The normal software around the model performs that action, so you still had to build the GitHub integration, the Gmail integration, the Jira integration, all of them. Now imagine your company builds another AI app that needs access to the same services. Without a standard interface, you may end up rebuilding those integrations again. And this is the problem MCP tries to solve. Instead of every AI application understanding every service differently, MCP gives them a common protocol. Your application connects to MCP servers. GitHub can have an MCP server. Notion can have one. Your database can have one. And they all expose their capabilities in the same format. Now here's the important part. An MCP server can tell the application what tools it provides. For GitHub that could be list issues, read pull requests, search code, create issue. This is called tool discovery. The application gives those available tools to the model. Then if you ask what bugs are still open for authentication, the model can decide that searching GitHub issues is the right action. It chooses the tool, your application sends the request through MCP, and the GitHub MCP server performs the operation. But underneath, that MCP server usually still calls GitHub's normal API. The API never disappeared. So does MCP replace APIs? No, APIs expose the actual functionality. MCP gives AI applications a standard way to discover and use that functionality. Think of APIs as the interface for software in general? And MCP is a common AI-facing layer built on top of them?

Do we really need MCP when we already have APIs? Let's understand the difference between the two. An API is how two pieces of software communicate. Let's say y…