MCP Dev Summit North America

MCP adoption is growing, but most agent integrations still treat tools as a prompt-time API, burning context tokens on tool definitions, re-copying intermediate results, and losing accuracy along the way. This improper use also leads to unfair criticism of MCP itself.

To address this problem, Cloudflare proposed MCP “code mode”: instead of prompt-time JSON tool calls, the model generates small programs that call tools via an API and run in a sandbox. This dramatically reduces overhead while improving accuracy in chained tool use. An alternative approach recently implemented by Cursor and Anthropic uses dynamic tool discovery to load only the relevant tools into context.

In this talk, we’ll introduce 𝚖𝚌𝚙𝚌 (https://github.com/apify/mcpc), a new open-source universal CLI client for MCP that brings both code mode and dynamic tool discovery to where they shine: the terminal. With persistent sessions, JSON output for scripting, and an MCP proxy for sandboxing, mcpc is an invaluable tool for AI engineers. We’ll live-demo a practical workflow that invokes multiple MCP servers in parallel, filters and transforms results locally, and then turns the interaction into reusable scripts.