The Model Context Protocol is the emerging 2026 standard for connecting AI agents to your data sources. Conceived by Anthropic, adopted by OpenAI and Microsoft: MCP changes how agents interact with the outside world.

The problem MCP solves

Before MCP, every AI agent had its own way of connecting to external tools. MCP proposes a universal protocol: an MCP server exposes tools and resources in a standard format any MCP client can use.

MCP architecture
MCP: a universal protocol between AI agents and data sources
500+
MCP servers available in open source
1 standard
to replace dozens of ad hoc integrations
Native support
in Claude, Cursor, Continue, Cline

Key concepts

Tools

An MCP tool is a function the agent can call: search a file, run a SQL query, send an email. Each tool has a name, a natural language description and a JSON schema for parameters.

Resources

Resources are data the agent can read passively: file contents, a web page, a database record.

Simple analogy: think of MCP as a universal USB-C connector. Your AI agent is the computer. MCP servers are the devices. The protocol is the USB-C standard.

Build your first MCP server in Python

Install the SDK: pip install mcp. Create your server with @server.tool() to define your tools. Add your server to Claude Desktop or Cursor config. Your tools are immediately available.

Essential MCP servers

MCP Filesystem, MCP PostgreSQL, MCP Slack, MCP GitHub, MCP Brave Search. All open source, all free.

MCP AI Agents Protocol Anthropic Integration Open Source

With care,

Sylvie Wendkuni NITIEMA
Founder & Data Scientist · DataSAI