MCP Toolkit
A small collection of MCP servers for connecting AI agents to everyday developer tools.
A set of minimal Model Context Protocol servers built to understand how MCP structures the connection between AI agents and external tools, compared to writing traditional API integrations by hand.
Most explanations of MCP stay conceptual. Building a few servers myself was the fastest way to actually understand the protocol's shape.
Small, focused MCP servers exposing a handful of tools each — file search, a notes lookup, and a simple task tool — following the protocol's resource and tool conventions.
- Multiple standalone MCP servers with narrow, well-defined tools
- Consistent error handling and structured tool responses
- Local test harness for exercising tools without a full agent runtime
TypeScript servers implementing the MCP spec directly, run locally and connected to an MCP-compatible client for testing.
Understanding the right granularity for a 'tool' — too broad and the agent loses control, too narrow and every task needs many round trips.
A clearer mental model of how MCP differs from a REST API: it's less about the transport and more about giving an agent a well-scoped, self-describing set of capabilities.