Our agent runs in the cloud, but our users’ spreadsheets live on their laptops. How do you bridge that gap?

The Model Context Protocol (MCP) is an open source standard introduced by Anthropic in November 2024 to standardize how AI models connect to external data and tools. MCP follows a client-server architecture where an MCP host, an AI application like Amazon Quick or Claude Code, establishes connections to one or more MCP servers. The MCP protocol supports two transport mechanisms: stdio (standard I/O for communication between local processes on the same machine) and streamable HTTP transport (HTTP-based communication between remote servers and clients). A missing piece is when the MCP server exists locally and the MCP client is remote.

This pattern matters for financial managers and analysts who primarily work with Excel and local files. They can use centrally deployed AI agents to act on those files while also drawing context from their browser. This is the same pattern that powers products like Claude Cowork, a cloud agent calling local tools through MCP, but fully self-hosted on AWS with your own model and custom tool servers. Internally, we built a production-grade AI assistant for finance that has seen over 41,000 conversations within a year since launch.