Soon, more agents than humans will use your product via MCP. Spanly gives you full observability on the MCP server you ship: error rates, session traces, latency, client analytics, deploy alerts. Drop-in CLI or SDK. US & EU data residency. Built for SaaS engineering teams shipping MCP in production, alongside the Datadog, Sentry, or New Relic you already run.
Hi!
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 likely 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!
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 analytics, with a Product view for PMs next to the Engineering view
- Alerts when a deploy spikes errors
- Data stored in the US or in the EU
The CLI and SDKs are open source (Apache 2.0). The cloud is paid: free up to 100k requests per month, plans from $49 with graduated volume pricing. Enterprise features (SSO, audit logs) on higher tiers.
Would love your feedback!
This is timely. I ship an MCP server, and my blind spot is tool-level, not transport. I want to see which tools agents actually reach for versus the ones I built that never get touched, plus the shape of the arguments they pass, because that would change what I cut and what I harden far more than p95 would. Are you capturing per-tool call analytics and argument patterns, or mostly session traces and latency right now?
About Spanly on Product Hunt
“See what AI agents do inside your MCP server”
Spanly launched on Product Hunt on June 17th, 2026 and earned 76 upvotes and 2 comments, placing #36 on the daily leaderboard. Soon, more agents than humans will use your product via MCP. Spanly gives you full observability on the MCP server you ship: error rates, session traces, latency, client analytics, deploy alerts. Drop-in CLI or SDK. US & EU data residency. Built for SaaS engineering teams shipping MCP in production, alongside the Datadog, Sentry, or New Relic you already run.
Spanly was featured in SaaS (43k followers), Developer Tools (515.4k followers), Artificial Intelligence (473.1k followers) and GitHub (41.3k followers) on Product Hunt. Together, these topics include over 253.7k products, making this a competitive space to launch in.
Who hunted Spanly?
Spanly was hunted by Tim Quinteiro. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
Want to see how Spanly stacked up against nearby launches in real time? Check out the live launch dashboard for upvote speed charts, proximity comparisons, and more analytics.
Tim Quinteiro