MCP in 3 minutes: what it is and why it matters

MCP stands for Model Context Protocol. Anthropic released it in late 2024 as a standard way for AI models to interact with external tools and data sources.

If you've used Claude Code with tools like file readers, web search, or database queries — you've used MCP under the hood.

How it works

An MCP server exposes a set of "tools" that an AI agent can call. Each tool has a name, a description, and a JSON schema for its inputs. The agent decides when to call a tool based on what it's trying to do.

Example: a ValorBrain MCP server exposes tools like search, store, whoami. When you ask your agent "what did we decide about billing last week?", it calls search with that query. The server returns relevant documents. The agent synthesizes an answer.

Why it matters for teams

Before MCP, every AI tool integration was custom. You'd write a specific plugin for Cursor, a different one for Claude Code, another for Kiro. Each with its own auth, its own API, its own quirks.

MCP gives you one server that works with every compliant agent. Write the integration once, use it everywhere.

ValorBrain and MCP

ValorBrain is an MCP server. Your agents connect to it like they'd connect to any MCP server — through config files or environment variables. The difference is that ValorBrain adds multi-tenancy, persistent memory, and cross-agent knowledge sharing on top of the basic protocol.

Your Claude Code session writes a decision. Your Cursor session reads it. Both use standard MCP tools. No custom integration needed.