MCP's Real Value Is Distributing Context, Not Just Calling Tools

MCP is often seen as an RPC layer for AI agents to call external tools, but its more powerful use is distributing context, rules, and workflows before work starts. This approach addresses limitations of RAG and local prompts by providing a governed, team-level environment. It ensures AI clients start with shared operating contracts, improving consistency and reducing reliance on individual prompt craftsmanship.