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TGGET Niche Research MCP Server

answering

TGGET Niche Research is answering right now. Last checked 8 min ago. It exposes 10 tools. Last commit 29 Sep 2026.

Validate app and SaaS ideas: search demand, competitors, app store data and a verdict.

Uptime history 26 days of history · worst day 99%
26 days agonow
100.0%
Uptime 24h
91 of 91 checks
10
Tools
read from the server
572 ms
Response time
average over 24h
0
Stars
last commit 29 Sep 2026

What changed 12

Every tool that appeared, vanished or quietly changed what it asks for. Recorded since 7 October 2026. No other catalogue keeps this.

7 Oct 5 tool descriptions were rewritten10 times that day compare_research, follow_niche, get_research and 2 more
7 Oct a tool changed the parameters it asks for2 times that day start_research
and 6 more, back to 7 October 2026

Nothing serious here today

Today is the operative word: we check TGGET Niche Research every 15 minutes and re-read its code on every release. Watch it and you find out the day that stops being true.

Three servers free · no card

Connect this server

Endpoint below is the one we actually reach during checks — not the one copied from a README. Last verified 8 min ago.

run in your terminal
claude mcp add niche-research --transport http https://tgget.io/mcp
Settings → Connectors → Add custom connector, then paste this address
https://tgget.io/mcp
~/.codex/config.toml
[mcp_servers.niche-research]
url = "https://tgget.io/mcp"
.cursor/mcp.json
{
  "mcpServers": {
    "niche-research": {
      "url": "https://tgget.io/mcp"
    }
  }
}
.vscode/mcp.json
{
  "servers": {
    "niche-research": {
      "type": "http",
      "url": "https://tgget.io/mcp"
    }
  }
}

Available tools 10

Read directly from the server with tools/list, grouped by what they act on. If a tool disappears, we record the date.

project
get_project
Returns a followed niche with the history of its checks, newest first: the first measurement (`baseline`) and the monthly checks, each with its numbers, what changed since the previous check and the id of the research it came from. Pass that `research_id` to get_report to read the fresh report of a check. Changes are computed from numbers and lists, not written by a language model.
update_project
Pauses a followed niche (`paused`: no monthly checks, its place in the plan is freed), follows it again (`active`, needs a free place in the plan) or stops following it (`deleted`: the project with its checks and digests is removed for good, the researches stay in the history). Ask the person before deleting.
research
get_research
Returns the current state and findings of a research by id: status, `country` and `language` the demand was measured in (null where a source does not measure by country), headline numbers, ranked candidate phrases, competitor overview, child researches (sub-topics, competitor checks, signals) with their ids, and skipped stages. Call repeatedly until status is completed and pending is 0.
list_research
Lists the researches the account started itself, newest first: niche scans of a phrase and descriptions of an idea, without the checks they spawned. Use it to find the id of an earlier research before get_research, get_report, compare_research or follow_niche, or to see what is still running. Each item has `id`, `kind`, `phrase`, `status` (queued, running, completed, failed), `mode`, `country` and `language` the demand was measured in, `created_at`, `url` of its page and `total_count`: monthly searches of the phrase, null for a description. `quota` tells how many researches the plan has left. Reads only; spends nothing.
compare
compare_research
Puts two to five finished niche scans side by side to help choose between ideas. `items` are the niches with their numbers, the report's positioning and napkin economics, and `wins`: in how many rows the niche holds the better value. `rows` are the ranked measures (verdict, demand, trend, cost per click, weak search results, competitor sites, App Store apps, fresh community signals) with the value of every niche and `best`, the indexes of the items that hold the better value; `better` says which way is better (max or min), null when the row is shown but not ranked. Every item names the `country` and the `language` its demand was measured in; demand and cost per click are not ranked across different markets, countries or languages (`mixed_markets`). The marks are computed from numbers, not written by a language model. Every scan needs a finished report. `share_url` is a read-only link to this comparison that works without signing in: give it to the person only when they want to share the comparison, it shows the numbers and the conclusions of their researches to whoever holds it.
follow
follow_niche
Starts following the niche of a finished scan that has a report: the scan becomes the first measurement and the niche is scanned anew every month, with a digest of what changed sent to the account. Monthly checks do not spend researches; the plan limits how many niches are followed (FREE 1, Starter 2, Pro 10). Following a niche that is already followed returns its project. The niche is followed in the country and the language its scan was measured in (`country` and `language` of the project), so every monthly check measures the same audience.
projects
list_projects
Lists the niches the account follows. A followed niche (a project) is scanned anew once a month and compared with its previous check. For each project: status, whether the plan serves it, the date of the next check, the latest numbers (verdict, demand, cost per click, competitor sites, App Store, community signals) and what changed at the latest monthly check, as structured `changes` and as `digest` lines of text. Also returns how many niches the plan follows.
report
get_report
Returns the final niche report of a finished scan (or the report research itself) as Markdown: verdict, what product to build (customer pains with evidence and severity, positioning, MVP with the pain each feature relieves, platform, monetization, competitor matrix), napkin economics (price hypothesis, acquisition cost from the cost per click in paid search, revenue per customer, whether it adds up, assumptions), SEO plan for the site (clusters, pages with title/H1/description, content plan, FAQ), ASO for App Store and Google Play, name options with domain and App Store availability, landing page draft, distribution channels by type with a first step, effort and priority, validation steps and risks. Pass format "json" for structured data (keys: verdict, product, economics, seo, aso, names, landing, channels, validation, risks).
signal
run_signal
Adds one check to a finished research and returns the id of the new child research. Use it when the scan skipped a stage, when a person asks about one phrase in particular, or to rebuild the report after new checks. A niche scan already runs the usual checks by itself, so this tool is for what is missing. Checks added this way are free: they do not spend researches of the plan. Checks of a demand research (`kind`): - `competitors`: who holds the search results for a phrase of the research; pass the phrase in `phrase`. - `dynamics`: two years of demand history. - `appstore`: App Store apps for the phrase with ratings and freshness. - `wiki`, `radar`, `youtube`: public interest and community signals. - `paid`: paid search for the phrase and its strongest candidates: volume, advertiser competition, cost per click. - `insight`: a summary of the findings written by the language model. - `report`: the final niche report, written anew from the current data; needs a finished niche scan. Checks of a child research: - `fingerprint`: product sites found by a competitors check, with pricing and app links; the parent is that competitors check. - `reviews`: recent App Store reviews of the leaders; the parent is an App Store research. - `insight` also accepts a competitors check as the parent. The parent must be completed and belong to the account. The check runs in the background: poll get_research with the returned `id` every 20-30 seconds until `status` is `completed`. `insight` and `report` are rebuilt at most once an hour.
start
start_research
Starts a niche research from a short search phrase or a plain-language description of an app or service idea. A phrase is scanned directly (demand, sub-topics, competitors, signals); a description is first turned into real search queries, the best one is then scanned automatically. Demand is measured in one country and one language: `country` and `language` when given, otherwise the country and the language of the phrase (English: United States, Spanish: Spain, Portuguese: Brazil); write the phrase in the language people search in there. `country` and `language` of the answer tell how the numbers were measured. Returns the research id to poll with get_research. Counts as one research of the plan allowance, whether the data comes from the sources or from the shared cache.

Endpoints

URLTransportStateLatencyChecked
https://tgget.io/mcp streamable-http answering 461 ms 8 min ago

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TGGET Niche Research — questions

Answers built from our own checks of this server.

What can TGGET Niche Research do?
It exposes 10 tools, read directly from the server on our last check. Among them: compare_research, follow_niche, get_project, get_report, get_research, list_projects and 4 more. The full list with descriptions is on this page — we take it from the server itself via tools/list, not from a README. How MCP servers expose tools in the first place →
What is TGGET Niche Research mostly used for?
Its tools cluster around project and research. That is what this server is built to work with — the grouping comes from the actual tool names, not from a category we assigned.
Is TGGET Niche Research working right now?
We send a real MCP handshake every 15 minutes. Over the last 24 hours 91 of 91 checks got a reply (100.0%), average response time 572 ms. The bar chart above shows every period we have measured.
How do I connect TGGET Niche Research?
Copy the ready config from this page. We generate it for Claude Code, Claude Desktop, Codex, Cursor and VS Code, each in the form that client actually reads. It is a remote server, so there is nothing to install — the client connects to the address.
Does TGGET Niche Research need an API key?
No. TGGET Niche Research completed a full MCP handshake with us as an anonymous client and listed its tools without asking for anything. All 10 of them are readable on this page. This is what we observed, not what the docs claim.
How fast is TGGET Niche Research?
It answers our handshake in 572 ms on average, which is faster than 22% of all working MCP servers we measure. That is on the slow side — worth knowing if the tool sits inside an interactive loop. The comparison comes from our own checks across the whole registry, every 15 minutes.
Is TGGET Niche Research open source?
We cannot say either way: 0 stars on GitHub, but we could not determine the licence, and without one the code is not open source by default.