creator-growth-intel

An MCP server that answers questions about creator marketing, UGC programs, influencer pricing and app growth from what working operators actually said in public, with a verbatim quote and a permalink on every answer.

It is built to be boring in one specific way: it never answers from nothing. When the corpus does not cover something, it says so instead of filling the gap.

7,111 claims  ·  926 operators  ·  1,989 of them contain a hard number
82% posted in the last two years  ·  every claim carries a quote and a link

Install

Two steps, and there is no third:

git clone https://github.com/dylanpakd-cyber/creator-growth-intel.git
claude mcp add creator-growth-intel -- node "$(pwd)/creator-growth-intel/mcp/server.mjs"

Clone it wherever you like; nothing is hardcoded to a path. data/intel.db is gitignored because it is derived, and the server builds it on first use in a few seconds. You never run a build by hand.

Requires Node 22+ (the server opens node:sqlite). No dependencies, no install step. Works with any MCP client, not just Claude Code.

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What it is good at

Ranked by how many distinct operators speak to each subject, which matters more than claim count: twenty people independently saying a thing is evidence, one person saying it twenty times is a hobby horse.

subject	operators	claims	ask it
pricing	229	544	what a creator costs, per post or per thousand, and how deals get structured
measurement	200	669	what to track, what people actually saw, where attribution breaks
angle-testing	199	976	how many creatives to run, how to find a winner, when to kill one
platform-tactics	182	659	what works on TikTok vs Reels vs Shorts, and what stopped working
briefing-and-creative	157	715	what to put in a brief, how much to script, how much to leave alone
volume-and-cadence	137	439	how many posts, how often, over how long
hooks-and-scripting	132	720	first three seconds, retention, how people open
deal-terms	126	285	exclusivity, usage rights, revisions, kill fees, who owns what
creator-side-view	122	163	what makes creators say yes, ghost, or walk. The other side of the table
sourcing	109	238	where people find creators and how they filter them

Good questions to open with:

• "How much do brands pay creators per thousand views for a managed program?"
• "How many creatives do people test before finding a winner?"
• "What do operators say about paying creators upfront?"
• "How much extra do people pay for usage rights or whitelisting?"
• "What stopped working on TikTok in the last year?"
• "What makes UGC creators walk away from a deal?"

The single most useful habit: call coverage_for before you trust an answer. It tells you how many operators actually speak to a subject, and flags it as THIN when the answer would be one person's opinion wearing a corpus costume.

What it does that nothing else does

Rate questions, because it refuses to pool four different economies into one number.

"CPM" names four unrelated markets in this corpus. About a third of rate-bearing claims are a platform paying a creator out of ad revenue, not a brand buying one. Their medians sit an order of magnitude apart. Pool them and the answer inverts. So on any rate question, pass rail:

rail	what it is	is it what a brand pays?
BUY	a brand or agency pays a creator per 1,000 delivered	yes, this is the one you want
PLAT	a platform pays a creator out of ad revenue (AdSense RPM, Creator Fund, Reels bonuses)	no, a different market
ADBENCH	what Meta or programmatic ads cost per 1,000	no, an alternative-channel anchor
REV	revenue earned per 1,000 views	no, a ceiling on what you can afford

Inside BUY, pass buy_type too, because it moves the median by more than an order of magnitude and a figure blended across types is meaningless:

buy_type	claims	operators	what it is
PROGRAM	44	28	a managed roster of briefed creators paid a set rate per thousand
CLIP	24	15	an open per-1,000 bounty on clips, usually capped per post
KOL	13	10	one sponsored post from an existing audience, priced as a fee
AMPLIFY / AGENCY	1 each	1	whitelisting; and an intermediary's pass-through price

Rail is hand adjudicated and deliberately partial (128 of 7,111 claims). A regex classifier was written for it and reproduced the hand labels on 22% of the set, because the split turns on meaning rather than vocabulary: "an RPM is set at $1.50" is a brand paying, "at a $10 RPM a creator earns" is a platform paying. It was deleted rather than shipped behind a confident interface. Unadjudicated claims carry a null rail, never a guess, and the server tells you when you are looking at the adjudicated slice.

What it is weak at, stated plainly

subject	operators	why it is thin
agency-vs-inhouse	22	barely discussed publicly, and the people who know are selling one of the two
attribution	33	the hardest problem in the space and the least honestly written about
failure-modes	45	survivorship. People post what worked

Also true, and worth knowing before you rely on it:

• It is keyword search, not semantic. "Why creators ghost" will surface "hire 50 ghost creators". Results covering less than half your question are labelled WEAK MATCH, but read the quote, not just the summary.
• claim_text is a machine-written summary. The quote is the authority. Claims were extracted by a language model behind a fabrication gate that rejects roughly 2% of candidates, so some slip through. If the summary and the quote disagree, the quote wins, and please open an issue.
• Self-selected sources. Operators who post publicly are not a random sample, and many sell courses, services or software in this category. A rate they quote is an interested number.
• Some concentration. The largest single contributor is 9.5% of claims and the top six are about a third. coverage_for exists so you can see whether a subject rests on many people or a few.
• Known blind spots ship with it. corpus_stats lists them. The headline one: brand-buy rates in traditional finance are n=0. Absence here means these operators did not say it publicly, not that it is false.

The three tools

tool	use it for
search_claims	the main one. Filters: topic, operator, claim_type, rail, buy_type, niche, limit
coverage_for	how well-evidenced a subject is, BEFORE you trust an answer about it
corpus_stats	what is in here and, more usefully, what is missing

claim_type is worth filtering on: number (1,989) for hard figures, tactic (2,392) for how-to, heuristic (1,755) for rules of thumb, warning (566) for what went wrong, tool (273), opinion (136).

niche is harvest provenance, not a content vertical. micro-pricing is the rate sweep, not a finance sweep, and a claim about any vertical can sit in any slice.

Attribution and removal

Every claim links to the original public post. Credit belongs to the authors, who did the work and wrote it down. Only extracted claims ship here, each as a quote plus a link; no raw archives are redistributed.

If you are quoted here and want your material removed, open an issue and it will be taken out, no argument, no questions.

Layout

mcp/server.mjs      the server. three tools, zero dependencies
lib/store.mjs       schema and query escaping
bin/build.mjs       rebuilds data/intel.db. the server calls this for you
data/claims.jsonl   source of truth. if the db and this disagree, this is right
data/rails.jsonl    hand adjudications for rail and buy type
data/silence.jsonl  what the corpus is known NOT to contain

MIT licensed.