debugging-mcp-analytics
Debugging MCP analytics
Product analytics for MCP servers. A team ships an MCP server; the @posthog/mcp SDK
wraps it in one line; every tool call, agent intent, and failure lands in PostHog as a
$mcp_* event you can query, chart, alert on, and cluster — plus a dedicated dashboard. The
MCP-layer sibling of @posthog/ai.
The differentiator is intent: not "ran query_run 14 times" but "was trying to find a
churn cohort". Explicit non-goal: this does not replace LLM analytics / AI observability
— generation traces, prompt/response, and token cost belong there.
Status: beta, TypeScript and Python SDKs shipped, whole product still behind the
mcp-analytics early-access flag (products/mcp_analytics/frontend/featurePreviewGate.ts).
PostHog dogfoods it — its own MCP server instruments itself, and that data drives the
dashboard. Public tracking: mega-issue PostHog/posthog#64016, which is the live source
for roadmap and customer wishlist.