What Is the Model Context Protocol?
The Model Context Protocol (MCP) is an open standard introduced by Anthropic that defines how AI models connect to external tools, data sources, and services. Think of it as USB-C for AI — a universal connector that lets any agent plug into any tool without custom integration code.
Before MCP: The Integration Hell
Before MCP, every AI platform had its own tool format. OpenAI had function calling JSON schemas. Anthropic had tool use definitions. LangChain had its own tool abstraction. Building one tool meant writing three different wrappers. MCP collapses this to one standard.
How MCP Works
An MCP server exposes a set of tools and resources over a standardised protocol (JSON-RPC over stdio or SSE). An MCP client (your AI application) connects to the server, discovers available tools, and calls them. The server handles the actual execution and returns results in a standard format.
MCP in the Aamlaa Architecture
Level 4 of the Vamana Protocol is the MCP Agent Servers tier: external frameworks like OASIS, Hermes, and MiroFish plug into Aamlaa via HTTP MCP adapters. This gives Aamlaa users access to specialised agents (OASIS for social simulation, Hermes for self-improving code agents) without rebuilding them from scratch.
Building an MCP Server
An MCP server is straightforward to build: define your tools as JSON schemas with input/output types, implement the handlers, and expose them via the MCP SDK (available in TypeScript, Python, and Go). The Elasticsearch plugin suite Elastic Edge AI uses this pattern to expose its 16 AI plugins as MCP-compatible tools.
Why MCP Is the Right Bet in 2026
MCP has become the default tool protocol for most major AI platforms. Claude Desktop, many VS Code AI extensions, and a growing number of enterprise AI platforms support it. Building your tools MCP-compatible means they work across all of these without modification.