Server definition

Hash: sha256:77c6099b3e6de33601a187cba72c503bfd1831c0f7be0ded1a4e92a2859b11ea
What it is: What a remote MCP server returned when asked what it offers: 10 tools

The blob, as servednamed by its sha256

{
  "instructions": "TGGET researches niches for mobile apps and online services: search demand, sub-topics,\ncompetitors in search results, demand history, App Store apps and reviews, Wikipedia interest, community\nsignals and AI insights. Research runs asynchronously in the background.\n\nWorkflow: call `start_research` with a search phrase or a plain-language description of the idea. Then poll\n`get_research` with the returned id every 20-30 seconds until `status` is `completed` and `pending` is 0;\nfindings, children and competitors appear progressively. When the scan lists a `report`, call `get_report` for\nthe final recommendations. Use `run_signal` to add a specific check to a finished research. Researches are limited per account and counted at the start, cache or not: read the `tgget://quota` resource before starting many researches.\nReport findings as evidence, not certainty: search interest is not a customer count. To choose between ideas,\n`compare_research` puts two to five finished scans side by side and marks the better value of every measure.\n\nFollowed niches: `follow_niche` turns a finished scan with a report into a project that is scanned anew every month.\n`list_projects` and `get_project` give the latest numbers and what changed since the previous check; read the fresh\nreport of a check with `get_report` and the check's `research_id`. `update_project` pauses, resumes or deletes a\nproject. Monthly checks cannot be started on request.",
  "tools": [
    {
      "description": "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. Demand and cost per click are not ranked across different markets (`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.",
      "inputSchema": {
        "properties": {
          "ids": {
            "description": "Two to five ids of finished niche scans (or of their reports), as listed by list_research.",
            "items": {
              "type": "string"
            },
            "type": "array"
          }
        },
        "required": [
          "ids"
        ],
        "type": "object"
      },
      "name": "compare_research",
      "outputSchema": null
    },
    {
      "description": "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.",
      "inputSchema": {
        "properties": {
          "research_id": {
            "description": "Id of a finished niche scan, or of its report.",
            "type": "string"
          }
        },
        "required": [
          "research_id"
        ],
        "type": "object"
      },
      "name": "follow_niche",
      "outputSchema": null
    },
    {
      "description": "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.",
      "inputSchema": {
        "properties": {
          "id": {
            "description": "Project id listed by list_projects.",
            "type": "string"
          }
        },
        "required": [
          "id"
        ],
        "type": "object"
      },
      "name": "get_project",
      "outputSchema": null
    },
    {
      "description": "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).",
      "inputSchema": {
        "properties": {
          "format": {
            "description": "markdown (default) for reading, json for structured fields.",
            "enum": [
              "markdown",
              "json"
            ],
            "type": "string"
          },
          "id": {
            "description": "Id of the scan research (its latest report is returned) or of the report itself.",
            "type": "string"
          }
        },
        "required": [
          "id"
        ],
        "type": "object"
      },
      "name": "get_report",
      "outputSchema": null
    },
    {
      "description": "Returns the current state and findings of a research by id: status, 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.",
      "inputSchema": {
        "properties": {
          "id": {
            "description": "Research id returned by start_research or listed by list_research.",
            "type": "string"
          }
        },
        "required": [
          "id"
        ],
        "type": "object"
      },
      "name": "get_research",
      "outputSchema": null
    },
    {
      "description": "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.",
      "inputSchema": {
        "properties": {
          "limit": {
            "description": "How many projects to return, 1-50 (default 20).",
            "type": "integer"
          }
        },
        "type": "object"
      },
      "name": "list_projects",
      "outputSchema": null
    },
    {
      "description": "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`, `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.",
      "inputSchema": {
        "properties": {
          "limit": {
            "description": "How many researches to return, from 1 to 50. Default 10.",
            "maximum": 50,
            "minimum": 1,
            "type": "integer"
          }
        },
        "type": "object"
      },
      "name": "list_research",
      "outputSchema": null
    },
    {
      "description": "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.\n\nChecks of a demand research (`kind`):\n- `competitors`: who holds the search results for a phrase of the research; pass the phrase in `phrase`.\n- `dynamics`: two years of demand history.\n- `appstore`: App Store apps for the phrase with ratings and freshness.\n- `wiki`, `radar`, `youtube`: public interest and community signals.\n- `paid`: paid search for the phrase and its strongest candidates: volume, advertiser competition, cost per click.\n- `insight`: a summary of the findings written by the language model.\n- `report`: the final niche report, written anew from the current data; needs a finished niche scan.\n\nChecks of a child research:\n- `fingerprint`: product sites found by a competitors check, with pricing and app links; the parent is that competitors check.\n- `reviews`: recent App Store reviews of the leaders; the parent is an App Store research.\n- `insight` also accepts a competitors check as the parent.\n\nThe 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.",
      "inputSchema": {
        "properties": {
          "id": {
            "description": "Id of the completed research the check is added to, as returned by start_research, get_research or list_research.",
            "type": "string"
          },
          "kind": {
            "description": "Which check to add. competitors, dynamics, appstore, wiki, radar, youtube, paid and report need a demand research as the parent; fingerprint a competitors check; reviews an App Store research; insight a demand research or a competitors check.",
            "enum": [
              "competitors",
              "dynamics",
              "appstore",
              "wiki",
              "radar",
              "youtube",
              "paid",
              "fingerprint",
              "reviews",
              "insight",
              "report"
            ],
            "type": "string"
          },
          "locale": {
            "description": "Only for insight and report: language of the text. Defaults to the language the research was started with, then to the language of the account.",
            "enum": [
              "en"
            ],
            "type": "string"
          },
          "phrase": {
            "description": "Only for competitors: the phrase whose search results are checked, usually one of the candidate phrases of the parent. Defaults to the phrase of the parent. Ignored by the other checks.",
            "type": "string"
          }
        },
        "required": [
          "id",
          "kind"
        ],
        "type": "object"
      },
      "name": "run_signal",
      "outputSchema": null
    },
    {
      "description": "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. 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.",
      "inputSchema": {
        "properties": {
          "deep": {
            "description": "Deeper scan with more sub-topics and competitor checks. Available on plans that include it (Pro) and to administrators; counted as two researches.",
            "type": "boolean"
          },
          "locale": {
            "description": "Language of the conclusions and the final report. Defaults to the interface language of the account. Texts meant for the site and the stores are always written in the language of the market.",
            "enum": [
              "en"
            ],
            "type": "string"
          },
          "text": {
            "description": "Search phrase (e.g. \"expense tracker\") or a description of the idea in your own words, up to 400 characters.",
            "type": "string"
          }
        },
        "required": [
          "text"
        ],
        "type": "object"
      },
      "name": "start_research",
      "outputSchema": null
    },
    {
      "description": "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.",
      "inputSchema": {
        "properties": {
          "id": {
            "description": "Project id listed by list_projects.",
            "type": "string"
          },
          "status": {
            "description": "active, paused or deleted.",
            "enum": [
              "active",
              "paused",
              "deleted"
            ],
            "type": "string"
          }
        },
        "required": [
          "id",
          "status"
        ],
        "type": "object"
      },
      "name": "update_project",
      "outputSchema": null
    }
  ]
}

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