MCP servers are quickly becoming the standard way AI agents reach tools, but the ecosystem is still missing basic infrastructure plumbing: uptime monitoring, latency tracking, and forensic debugging. When an agent run fails, "the MCP server did something weird" is usually where the trail goes cold.
I wanted both tools to stay narrow and not overlap with things I'd already built (mcp-schema-watch
for schema drift, `skillcheck`
for SKILL.md linting, Swarm Trace Viewer for swarm-run analysis). So FleetWatch and MCP Blackbox split the job in half — one watches, one records.
FleetWatch pings your registered MCP servers on a schedule and tracks:
The moment a server goes down, degrades, or recovers, FleetWatch fires an alert. It's built with TypeScript, NestJS, and Next.js, communicates over WebSockets for live status updates, and ships with a full test suite plus a GitHub Actions CI workflow.
🔗 https://github.com/DIYA73/fleetwatch FleetWatch tells you something broke. MCP Blackbox tells you why.
It's a recording proxy that sits in front of your MCP traffic and captures full request/response payloads. The interesting design decision was around retention: instead of keeping everything (expensive) or nothing (useless when you actually need it), Blackbox permanently pins anything around a failure and prunes the rest. A flight recorder for your MCP servers — the data you need, right when you need it, without the storage bill of logging forever.
Same stack as FleetWatch — TypeScript, NestJS, Next.js, WebSockets — so the two integrate cleanly.
🔗 https://github.com/DIYA73/mcp-blackbox FleetWatch and MCP Blackbox are deliberately separate — you can run either one on its own. But paired together, the workflow is simple: FleetWatch catches the failure in real time, and Blackbox already has the trace waiting for you.
Both are open source and public on GitHub — issues, stars, and PRs are always welcome. If you're building on MCP and hitting the same "I have no idea what just happened" wall, I'd love to hear how you're solving it.