| Hi HN! I'm Tim, solo founder of Spanly. Since MCP got traction in early 2025, I've been convinced that within a few years, agents may use your product more than humans do, and if so, they'll mainly do it via MCP. Today, MCP monitoring often stops at the HTTP layer, and at best instruments the official SDK to gather a few more insights. You still can't observe any deployed MCP, get the overall view, the sessions, or the analytics. Spanly is my attempt to fill that gap! Live demo: https://app.spanly.com/share/demo CLI/SDK source (Apache-2.0): https://github.com/spanlyhq/spanly The key concept: capture every JSON-RPC request and response your MCP server handles. Put the Spanly CLI in front of any MCP server (or use the TypeScript/Python SDK) and get a live, organized view of all that traffic. - Error rates and p50/p95/p99 latency per tool, resource, prompt, etc... - Per-client, per-server, per-version views - Full session traces to replay what an agent did, with payload - Adoption and client analytics - Alerts when a deploy spikes errors - Data stored in the US or in the EU It blends with your existing Datadog/Sentry/New Relic through a deep-link. Under the hood this is built on top of ClickHouse, Postgres and Redis, is deployed on Render and payloads are stored in Cloudflare R2. SDKs and CLI are meant to be simple: packets are forwarded for ingestion. The heavy lifting happens in Spanly backend: pairing requests/responses, aggregating for sessions, extracting analytics and storage. An MCP is available for agents to debug your production MCP servers. As dog-fooding principle obliges, Spanly MCP is monitored by Spanly. This is my first solo project. Would love your feedback! Tim |