MCP (Model Context Protocol), introduced by Anthropic in late 2024 and adopted across the industry in 2025-26, standardises how language models discover and call external tools. Before MCP, every application that wanted to give an LLM access to a filesystem, a database, a Slack workspace, or a GitHub repo had to implement that integration from scratch — duplicate code, divergent semantics, and no portability between tools. MCP fixes this with a client–server protocol: tool providers ship an **MCP server** that exposes capabilities via a common schema, and any **MCP-compatible client** (Claude Desktop, Claude Code, Cursor, Windsurf, Continue, and a growing list of others) can use those capabilities without custom code.
The protocol itself is small and deliberately boring. An MCP server exposes three primitives: **tools** (callable functions the model can invoke), **resources** (readable content the model can pull into context), and **prompts** (reusable templates the user or client can invoke). Communication runs over stdio, HTTP, or WebSocket. The design choice that matters most is that MCP servers live outside the model — they can be written in any language, run anywhere, and be developed independently by people who have no LLM expertise.
The ecosystem grew fast. Official reference MCP servers exist for filesystems, SQLite, Postgres, GitHub, GitLab, Slack, Google Drive, Sentry, and dozens of other systems. The community catalogues on MCP marketplaces and awesome-MCP lists cross a thousand entries by 2026. For enterprises, the appeal is portability and vendor de-risking: tool integrations written against MCP outlive a switch between foundation-model vendors, and an internal tooling team can ship one MCP server that serves every AI surface the business cares about.
For APAC mid-market specifically, MCP simplifies the otherwise-ugly question of how to give Claude, Copilot, Cursor, and a custom internal agent all access to the same knowledge base without building four integrations. The near-term caveat is security posture — an MCP server is a wide tool surface; supply-chain vetting and capability scoping matter as much as they would for any other internal service that processes sensitive data.
Where AIMenta applies this
Service lines where this concept becomes a deliverable for clients.
Beyond this term
Where this concept ships in practice.
Encyclopedia entries name the moving parts. The links below show where AIMenta turns these concepts into engagements — across service pillars, industry verticals, and Asian markets.
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