We build an MCP gateway. That means we have to answer "where is the demand for MCP tooling" with
numbers instead of instinct — and when we finally measured it, the shape of the answer was not what
the topic's noise suggests. This is that measurement, with the method attached so anyone can repeat
it and disagree with our reading.
The MCP ecosystem produces a lot of content and very little demand data. Every week brings another
"awesome MCP servers" list, another protocol explainer, another launch post. What none of them carry is
the number that decides what to write next: how many people search for a given phrase in a month, and
how hard the results page for it is to enter.
We had a second reason to care. Our own pages were indexed, our sitemap was clean, and our Search
Console still showed almost no non-branded impressions. When that happens, the useful question is not
"is our prose good" but "does anyone search for this at all, and with what words". A demand
measurement answers both at once.
The pool comes from paid keyword data, not estimate tables scraped from a free tool:
The 73 phrases sum to 42,270 searches per month. One phrasing carries more than a quarter of it:
| Phrase | Monthly searches | Share of pool |
|---|---|---|
| model context protocol | 12,100 | 28.6% |
| mcp protocol | 4,400 | 10.4% |
| a2a protocol | 3,600 | 8.5% |
| mcp tools | 2,400 | 5.7% |
| agentic rag | 1,900 | 4.5% |
| mcp vs api | 1,900 | 4.5% |
| everything else (67 phrases) | 15,970 | 37.8% |
Two readings follow, and they point in opposite directions. The optimistic one: there is a real
audience — 42,000 searches a month is not a hobbyist niche. The pessimistic one: the top three phrases are 47.6% of it, and those three are the
Difficulty here is a 0–100 estimate of how hard the first page is to enter. Sort the pool by volume
and a pattern appears — the big phrases are defended, and the usable ones sit in the middle:
| Phrase | Monthly searches | Difficulty |
|---|---|---|
| anthropic mcp | 1,600 | 69 |
| mcp protocol | 4,400 | 64 |
| model context protocol | 12,100 | 58 |
| mcp tools | 2,400 | 56 |
| mcp spec | 1,300 | 32 |
| mcp server list | 880 | 22 |
| mcp vs api | 1,900 | 12 |
| streamable http | 880 | 12 |
The two phrases with the lowest difficulty in the whole table are also two of the most specific:
"mcp vs api" compares two architectures, and "streamable http" names one transport that MCP
standardised. Both are the kind of query a reader has after learning what MCP is, and both are
answerable by anyone who has actually shipped the thing rather than read the specification.
That asymmetry is the practical finding: the demand that a new entrant can realistically win is not the demand that looks biggest. Chasing the 12,100 phrase means competing with the protocol's
This was the surprise. We expected the 48 phrases to collapse into a handful of topical clusters, the
way "cheap flights" and "low cost flights" belong together. Instead, clustering the live result pages
turned 48 phrases into 43 clusters — with only 4 merges and 11 adjacent pairs across the whole set.
Translation: for MCP, almost every phrase owns its own result page. "mcp spec" and "mcp
specification" are not the same query if the results pages disagree; "mcp tools" and "mcp servers" sit
next to each other without merging. The topic looks like one huge subject from the outside and
behaves like a mosaic of small ones from the inside.
This has a direct consequence for anyone planning content here, and it is the opposite of the usual
advice to build one comprehensive pillar page. A single page cannot be the canonical answer to 43
different result pages. What works is a small centre per phrase family — the protocol overview, the
transport comparison, the client-configuration walkthrough — each one narrow enough to actually match
its result page, and each one linking to its neighbours so that a reader who lands on any of them can
reach the rest. Our own overview of the protocol's actors, lifecycle and transports is written to that
shape, rather than to a keyword count.
The last piece of the measurement is not about search demand at all; it is about what our own site
saw while we were publishing into this pool. In the four weeks ending 22 September 2026, our Search
Console recorded 54 impressions and 7 clicks — and every one of them was a branded query. Not one
of the non-branded phrases in the table above produced an impression during that window.
That is worth stating plainly, because it is the number that disciplines the rest: a pool of 42,270
monthly searches, fifty-odd published articles, and a non-branded impression count of zero. Demand
being real does not mean demand is reachable; the pages existed before the audience did, and Google has
to decide to serve them before any of the arithmetic in this article matters.
The same period's edge logs add a useful counterweight: of the page reads recorded at our CDN in one
week, 282 carried AI-crawler user agents and 144 carried search-crawler user agents. Treat that as a
signal rather than a measurement — a user agent is a claim, not an identity, and machine files like
robots.txt inflate both numbers unless they are filtered out. The direction is still informative:
agents are reading this material earlier and more often than search engines are.
Three things, all of them reversible if the next snapshot disagrees:
The honest list, because a demand table invites more confidence than it earns:
If the useful summary is one paragraph long, it is this: for MCP the measurable demand is real but concentrated in a handful of definitional queries, the entry price is lowest exactly where the
audience is most specific, and the topic fragments into far more result pages than its vocabulary
suggests. Plan accordingly — a few narrow pages that answer a phrase completely, linked into a
neighbourhood, will outperform one broad page that answers nothing precisely.
The pool, the clustering and the diffable snapshots stay where the content lives. If you want the
starting point rather than the summary, the protocol's own mechanics are documented in our
MCP overview, and the published-server side is collected in the
server list. Disclosure: this measurement was assembled and written with AI assistance from our own paid keyword requests and Search Console exports; the numbers are quoted from those files rather than re-typed.