GTM AI Index
Subscribers · Setup

Everything your license key opens

One key from your receipt opens the edition pack as a download, the index inside an assistant over MCP, and the same files by script on a schedule.

Your key is on your Lemon Squeezy receipt and under My Orders. Paste it once and every address and command below fills in, nothing to hand-replace.

It stays in this tab

The key is held on this page and checked once against the store by this site. Nothing else stores or sends it, and every address below is built in your browser. A key that arrives in the address from your receipt is taken out of the address bar as soon as it is in the field.

First of three · For anyone

Download the pack

The edition pack is the finished edition: the standing, every label with its evidence, every answer, and the category reports. The button produces a link that lasts ten minutes.

The pack
Paste your key to download

The button fills in as soon as the key is in the field above.

The category reports
Open the report

One PDF per category: the standing, the warnings, the sources and every answer, with a written summary. Or every report this key opens.

What is in it

standing.csv, labels.csv, responses.csv, prompts.csv, models.csv, vendors/<product>.csv, index.sqlite and the data dictionary in README.md.

Which reports a key opens

The Standard pack opens a report for every category. The Expanded pack opens the category on the subscription with the flagship models beside the standard tier, and the standard reports for the rest. By address: &report=list or &report=<category>.

Which edition you get

A subscription key opens the newest edition, or an earlier one with &edition=2026-09. A single-edition key opens the edition it was bought for.

Second of three · For a chat window

Connect an assistant

Every subscription includes the index as an MCP server. Add it to Claude, Cursor or any client that speaks the Model Context Protocol, and the assistant answers from the current edition, with the evidence quotes and the edition each answer came from.

https://gtm-ai-index.com/mcp/

The one string every client needs. Transport is streamable HTTP; there is no sign-in.

Three clients, not three steps: do the one that is yours.

Claude Desktop and Claude.ai

Custom connector
Fields to enter
Name           GTM AI Index
Address        https://gtm-ai-index.com/mcp/
Authentication No sign-in
Header name    Authorization
Header value   Bearer YOUR-LICENSE-KEY

Settings, Connectors, Add custom connector. Where the client offers no header field, use the address form in the third card.

Claude Code

One command
Terminal
claude mcp add --transport http gtm-ai-index https://gtm-ai-index.com/mcp/ \
  --header "Authorization: Bearer YOUR-LICENSE-KEY"

Cursor and other clients

Config file
mcp.json
{ "mcpServers": { "gtm-ai-index": {
    "url": "https://gtm-ai-index.com/mcp/",
    "headers": { "Authorization": "Bearer YOUR-LICENSE-KEY" } } } }

Where a client offers no headers, the key can go in the address: https://gtm-ai-index.com/mcp/YOUR-LICENSE-KEY. Treat that address as the key itself.

Third of three · For a pipeline

Fetch on a schedule

The pack downloads by address with the same key, so a pipeline can collect each edition on its own schedule. The key is checked against the store on every call.

One line, on a schedule
curl -L "https://gtm-ai-index.com/pack/download/?key=YOUR-LICENSE-KEY" -o pack.zip

The address answers with a redirect to a signed link that lives ten minutes; -L follows it. Add &edition=2026-09 for one month.

Ask for JSON instead
curl "https://gtm-ai-index.com/pack/download/?key=YOUR-LICENSE-KEY&format=json"

Returns the edition, the file name, its size and a signed URL with its expiry, and refusals as JSON with the same status codes. Useful for a step that decides before it downloads.

Know when a new edition is out
curl https://gtm-ai-index.com/pack.json

The public manifest lists every edition and needs no key. Poll it and download when a new edition key appears, or run on the second of each month: editions compile on the first.

Over MCP

What it answers

Eight tools over the edition the site currently serves. Every answer names the edition and the vendor table version, so the figure can be checked against the page.

ToolReturns
editionthe edition, its models, the vendor table version and the noise floor; cite it
list_categoriesevery category with its leader and share, per segment
category_standingthe ranked products in a category: share, rank, negative rate, each model's label, the products warned against, the prompts asked
model_pickswhat each model named first, as an alternative, and against, per prompt framing
vendor_standingone product across every category it holds a rank in, with how each model treats it
evidenceverbatim quotes for or against a product, each naming the model, the category and the framing
search_vendorsfind a product by its name or by a name a model wrote
movementchange since the previous edition, qualified against the noise floor; from the second edition on

A single-edition key opens the edition it was bought for, while the site serves that edition. A subscription key opens every edition as it publishes. The server reads the same files the site is built from, so it updates the moment an edition does.

Eight things to ask it

The same questions the pack files answer, asked in a chat window. Each card names the files behind the view; the tools above read those files, so the answer carries the edition and the vendor table version it came from.
01Battlecards

What does the model tell a buyer about us, and about the three products we lose to?

ModelYoursRival ARival BRival C
One cell per product per model: the label, and the quote behind it.

A matrix of product by model, each cell the label the model gave, with the verbatim quote under it. Objection handling written from what the buyer's assistant already said, refreshed monthly with nobody re-running the chats.

From labels.csv joined to responses.csv
02Retrieval

When the model recommended in our category, what did it read first?

Review siteComparison postYour siteForum threadVendor blog
Cited domains behind the answers, ranked.

Cited domains ranked per category, and your own domain's share of citations edition over edition. It shows which third-party pages carry the recommendation into the answer. That is a fact about retrieval, not a lever on the model.

From responses.csv, cited URLs where the model searched
03Buyer size

Are we the small-business pick and absent at enterprise, or the reverse?

SMBMid-marketEnterprise
Share by segment, three standings, never pooled.

The same category, computed three times, once per buyer segment. Positioning gets evidence from the buyer side of the screen: which size of company the assistant thinks the product is for.

From standing.csv, per segment
04Framings

Do we come up when the buyer asks plainly, only when budget is tight, or as the product to avoid?

DirParaCompBudgScaleNeg
One bar per framing, for one product.

Six bars per product, one per framing. The framing a product wins is the buying situation to sell into, and the negative framing is the objection list, sourced. The paraphrase pair says whether the answer survives a rewording.

From labels.csv by framing
05Movement

Did our standing move this month, and is the move bigger than noise?

Noise floor
Rank per edition, with the measured band drawn on it.

A rank timeline with the noise band drawn on it, and a movers table for the category. A single month's shift is usually inside the noise. The index says which ones are not, with the date and the model version attached.

From movement.csv, history.csv, models.csv
06In the deck

What have the assistants said in our favor, in words we can show a prospect?

Claude Opus 5 · directFirst choice
GPT-6 Astra · comparativeFirst choice
Gemini 3.1 Pro · budgetAlternative
Quotes stacked by model, each with the edition it came from.

Every label for one product, with the verbatim evidence quote, the model, the framing and the edition beside it. A slide can show what an assistant said rather than paraphrase it, and the number on the site can be traced to the same row.

From vendors/<product>.csv
07The whole index

Where is no product the consensus, and where are we named without being ranked?

ConsensusClear leaderContestedA product of yours appears
Marketing
Sales
Customer
Revenue operations
GTM data and infrastructure
Partner and channel
One square per category, 73 in all. The outlined squares stand for a subscriber's products; the verdicts are drawn by the build.

The verdict map: 73 categories by go-to-market function, colored by verdict. Category strategy from the assistant's point of view: where the field is settled, where it is not, and where a product is already in the conversation without leading it.

From standing.csv across all 73 categories, with the verdict per category
08By assistant

Which assistants recommend us, and do the flagship models say the same as the models on a free plan?

Twelve modelsThree products
Where they agree, and which assistant is the outlier.

An agreement matrix, model by product, and the standard run against the expanded one for your category. The answer a buyer hears depends on which assistant they opened, so a strong standing in three and none in the fourth is a specific, named gap.

From vendor_by_model.csv, plus the expanded run