As more of my tooling starts talking to MCP servers instead of calling APIs directly, I kept running into the same gap: there's no lightweight way to know when an MCP server goes down, and no way to see what actually happened when something breaks mid-run. So I built two small, focused tools to close that gap — FleetWatch and MCP Blackbox.
The problem
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:
