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Model Context Protocol (MCP) Explained: The New Standard for AI Agent Integration in 2026

Platform Team

Platform Team

January 10, 2026
7 min read
Model Context Protocol (MCP) Explained: The New Standard for AI Agent Integration in 2026

Model Context Protocol (MCP) Explained: The New Standard for AI Agent Integration in 2026

In December 2025, something remarkable happened. Anthropic donated the Model Context Protocol to the newly formed Agentic AI Foundation under the Linux Foundation. This move signaled MCP's evolution from a proprietary standard to the universal language for AI agents.

What is Model Context Protocol?

The Model Context Protocol (MCP) is an open standard introduced by Anthropic in November 2024 to standardize how AI systems integrate with external tools, data sources, and systems.

Think of MCP as USB for AI agents—a universal interface that allows any AI model to connect to any tool or data source.

Key Capabilities:

  • Reading files from local systems or cloud storage
  • Executing functions and API calls
  • Handling contextual prompts across sessions
  • Managing tool permissions and access control

Industry Adoption Timeline

DateMilestone
Nov 2024Anthropic introduces MCP
Mar 2025OpenAI officially adopts MCP
Apr 2025Google DeepMind confirms Gemini support
Dec 2025MCP donated to Linux Foundation
Jan 202675+ official connectors available

Why MCP Matters for Developers

Before MCP, connecting AI agents to external systems required custom integrations for each pairing. MCP provides:

  1. Standardization: One protocol for all integrations
  2. Portability: Switch between AI providers easily
  3. Security: Standardized permission models
  4. Ecosystem: Growing library of connectors

"MCP has been adopted by ChatGPT, Cursor, Gemini, Microsoft Copilot, Visual Studio Code, and other popular AI products." — Model Context Protocol Blog

MCP Security Considerations

In April 2025, security researchers identified several concerns:

  • Prompt injection vulnerabilities
  • Tool permission escalation
  • Lookalike tool substitution attacks

Best Practices:

  • Always verify tool authenticity
  • Implement least-privilege access
  • Monitor agent actions in production
  • Use enterprise-grade MCP servers

How Afelyon Uses MCP

At Afelyon, we leverage MCP for seamless integrations:

  • Jira & ClickUp: Read tickets via MCP connectors
  • GitHub: Create PRs with proper context
  • Slack: Send notifications through MCP
  • Your Codebase: Deep integration with repositories

The Result:

An AI agent that understands your entire development ecosystem and can act autonomously within it.

Building with MCP

If you're building AI-powered tools, MCP support is now essential. Resources:

The Future of AI Integration

With OpenAI, Google, Microsoft, and Anthropic all supporting MCP, it's becoming the de facto standard for AI agent development. Companies building AI tools without MCP support risk isolation from the broader ecosystem.


Experience MCP-powered development with Afelyon. Our AI agent uses MCP to connect seamlessly with your tools.

Related:

mcpmodel-context-protocolanthropicai-integrationstandards

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