I checked every MCP server in the official registry. About 1 in 10 is broken.

There is a number going around that roughly half of all remote MCP servers are dead.

I had repeated it myself, in the README of a tool I published. I could not find where it came from, so I measured it.

The answer is that about one in ten is actually broken. The number traces to an April 2026 analysis of 2,181 remote endpoints. Mine covers a different population three months later, and the gap is mostly that — not a mistake by whoever ran it.

Here is the method and the full breakdown.

What I measured

On 29 July 2026 I pulled every entry from the official MCP registry — 1,200 servers. Of those, 297 had status: active and advertised a remote endpoint URL (the rest are stdio/local packages with nothing to probe over the network).

Each got one anonymous JSON-RPC initialize over streamable HTTP, with a 10 second timeout:

{
  "jsonrpc": "2.0", "id": 1, "method": "initialize",
  "params": {
    "protocolVersion": "2025-06-18",
    "capabilities": {},
    "clientInfo": {"name": "mcp-uptime", "version": "0.1.0"}
  }
}

Then I classified the response: a valid result containing protocolVersion or serverInfo is up, 401/403 is auth-gated, and everything else got bucketed by its actual failure.

Results (n = 297)

Result	Count	Share
Completed an MCP handshake	133	44.8%
Auth-gated (401/403)	134	45.1%
DNS failure	8	2.7%
Server error (5xx)	6	2.0%
Not found (404/410)	5	1.7%
Redirect (307/308)	4	1.3%
Timeout	2	0.7%
Non-MCP response	2	0.7%
Other (400, 405, connection)	3	1.0%

Reachable: 267 (89.9%). Genuinely broken: 30 (10.1%).

Where "half are dead" comes from

Look at the first two rows. 55.2% of these endpoints will not complete an anonymous handshake — and that is suspiciously close to the number people quote.

But 134 of those 164 are returning a clean 401 or 403. They are running. They are answering. They want an API key, which is a completely reasonable thing for a hosted service to want.

Whether the original analysis counted those as dead I genuinely don't know — I can't see its raw data. What I can say is that on the population I measured, treating auth-gated servers as down would inflate the failure rate about fivefold, and the two figures are not measuring the same thing: 2,181 endpoints found in the wild in April versus 297 registry-listed active servers in July. A curated registry should be healthier than a broad crawl, and three months is a long time in this ecosystem. If you want the honest one-liner: the registry is in better shape than the wider endpoint population was in April, and 'half of MCP is dead' does not describe what is in the registry today.

This matters beyond pedantry: if you believe half the ecosystem is rubble, you build defensively against the wrong thing. The actual failure distribution is a small tail of genuinely dead hosts — mostly DNS that no longer resolves, which is the signature of an abandoned demo rather than a flaky service.

The failure the number doesn't capture

Liveness is the easy question, and it is not the one that will hurt you.

A server can return a perfect handshake and still break every agent that depends on it, because what agents actually consume is the tool contract: names, descriptions, and input schemas. Rename a tool, add a required parameter, tighten an enum — the endpoint stays green and your agent fails at call time, mid-run, looking for all the world like a model error.

Downtime is loud. Schema drift is silent, and it surfaces as "the AI is being weird today."

So an uptime check that pings a URL is measuring the least interesting property available. What you want to watch is whether the tool inventory and schemas changed since the last time you looked.

Caveats, stated plainly

• An anonymous handshake is a lower bound. Auth-gated servers might also be broken behind their auth wall. I cannot see past it and am not claiming otherwise — 10.1% is the floor for "broken", not a ceiling.
• One probe, one moment. A server that was timing out at 14:00 UTC may be fine now. This is a snapshot, not an uptime percentage.
• Registry-listed only. Plenty of MCP servers are never registered; this says nothing about them.
• Redirects counted as not-usable. Four servers returned 307/308. A tolerant client would follow them. I did not, because following redirects blindly is how an endpoint checker becomes an SSRF vector.

Reproduce it

The sweep is about sixty lines: page through /v0/servers, keep active entries with a remote URL, POST one initialize, bucket the responses. If you run it and get materially different numbers, I would genuinely like to know.

I also published the checker as a free tool — it does the handshake, the tool inventory, and the schema-drift comparison, as a live MCP server (io.github.park11innyc-lgtm/mcp-uptime in the registry) and as an Apify Actor. No auth, no cost.

The general lesson

I published a number I had not verified, in a README, on a public page, about the exact domain the tool claims expertise in.

That is the same mistake I keep writing about from other angles: trusting a status field instead of the artifact, and the operational parts of MCP that tutorials skip. A widely-repeated statistic is a status field. It feels like knowledge and it is actually someone else's unverified claim, forwarded.

Measuring it took under an hour.

Comments

[Mads Hansen]

Good correction, and unusually clear caveats. I’d avoid collapsing the checker’s result into reachable/broken even internally. Track four orthogonal states: transport reachability (DNS/TLS/HTTP), protocol negotiation, authenticated functional behavior, and contract compatibility. A 401 is positive evidence for the first two and unknown for the latter two; a redirect is a policy decision, not automatically downtime.

Repeated probes across time and regions would add a useful transition matrix to the snapshot. Redirects can also be followed safely with an SSRF-hardened resolver: resolve every hop, reject private/link-local/metadata ranges before connection, verify the actual connected peer, cap hops, and revalidate DNS.

Then fingerprint tools/list canonically—stable sort, normalized JSON Schema, digest—and use a test credential for a harmless canary call. Alert severity can reflect which axis regressed. That gives server owners an actionable SLO while giving consumers a more honest availability signal.