If you've built an AI agent, you know the drill. You need Jira access, so you write a wrapper. Then Postgres. Then Slack. By the time you're done, you're maintaining integration code instead of building product.
Model Context Protocol (MCP), Anthropic's open standard from late 2024, addresses this. The protocol separates AI clients (Claude Desktop, Cursor, your custom app) from MCP servers: small programs that expose specific capabilities. When the client connects, the server declares what it can do. The client uses those capabilities. No custom integration required.
The architecture is straightforward. An MCP server offers three things: Resources (read-only data like schemas), Tools (actions the AI can trigger), and Prompts (instruction templates). The AI sees what's available and calls what it needs. Security is handled by exposure control: you choose which functions to surface.
Here's what a basic Python server looks like using FastMCP:
from mcp.server.fastmcp import FastMCP
mcp = FastMCP("NotesReader")
@mcp.tool()
def read_note(filename: str) -> str:
with open(f"./notes/{filename}.txt", "r") as f:
return f.read()
That's it. Any MCP-compliant client can now read your notes, regardless of what language the client is written in.
Early adoption has been significant. Block, Apollo, Zed, Replit, Codeium, and Sourcegraph integrated MCP shortly after launch. Thousands of community-built servers now exist, with SDKs available for major languages. GitHub hosts the spec and reference implementations.
The trade-offs matter here. You're adding another layer to your stack. For teams building multiple AI agents or maintaining numerous integrations, that trade-off makes sense. The alternative is maintaining N×M custom connectors as your tool count grows.
Three implications for CTOs: First, portability across AI platforms without rewriting integrations. Second, security through controlled exposure rather than direct access. Third, centralized maintenance when APIs change.
The ecosystem is still maturing. Enterprise-scale deployments will reveal where the protocol needs refinement. But the fundamental problem it solves, the NxM integration challenge, is real. We'll see whether the community coalesces around this standard or fragments into competing approaches.
For now, the MCP server directory has pre-built connectors. Claude Desktop supports it natively. Worth testing if you're building agents at scale.