What metrics would you instrument to evaluate the health of a production MCP integration?

An MCP integration has several moving parts, and one global number hides where things break. So you instrument it in layers. The first layer is **protocol health**. Can the host even connect to the server? Watch how long the `initialize` handshake takes and whether servers stay reachable. A server that fails to start drops all of its tools at once. The second layer is tool execution. For each tool, track how often a `tools/call` succeeds, how fast it responds, and which JSON-RPC error codes come back. Slice these per tool, not globally, because one slow tool can hide behind ninety fast ones. The third layer is user trust. MCP asks the user to approve tool calls. If the rejection rate suddenly climbs, users are getting suspicious, which can signal a tool that quietly changed its behavior or is now asking for too much. Finally, wire alerts on each layer and put them on one dashboard. There is no built-in MCP metrics standard, so you define the schema yourself.

I instrument three layers, and I slice everything per server and per tool. **Protocol health** comes first. I track session establishment time, the `initialize` handshake duration, and server availability. A rising handshake time hints at version negotiation regressions. A downed server takes all of its tools with it. **Execution health** is the core. Per tool I track `tools/call` success rate, latency percentiles like p50, p95, and p99, and the distribution of JSON-RPC error codes. A p99 spike on one tool usually means an external dependency or a rate limit. A burst of -32601 means method not found, often server version drift. A burst of -32700, parse error, points at schema evolution bugs. The third layer is the **approval funnel**. MCP makes the user approve tool calls. I track the approval to rejection ratio per tool. A rising rejection rate is a trust signal. It can mean a tool changed its description or now asks for broader scope, a classic rug pull or tool-poisoning symptom. There is no standard MCP observability schema, so I define one. I tag every metric with server name, tool name, and protocol version, then alert per layer and render it all on one dashboard.