MCP Testing
Also known as: Model Context Protocol Testing
MCP testing verifies implementations of the Model Context Protocol — the standard that lets AI models discover and call external tools and data sources — checking that a server correctly exposes its tools, and that a client correctly discovers, calls, and handles responses from them.
Because MCP defines a standardized interface between models and external tools, testing spans both sides: on the server side, confirming tool definitions are accurate and well-described (a model can only use a tool correctly if its description accurately reflects what it does and expects), and on the client side, confirming the model correctly selects and invokes the right tool for a given task.
As an emerging, actively evolving standard, MCP testing also needs to account for protocol-version compatibility and graceful handling of tools that fail, time out, or return unexpected data — much like testing any API integration, but with an AI model in the calling role instead of a deterministic client.
