mcp server
HyperStore
Search and inspect 6,500+ curated AI apps from the HyperStore directory.
Description as published by the maintainer. Source
- version 0.1.1
- active
- retrieval
active — Most recent push to the repository was 2026-06-20. Dashed tags are derived by ZBS Index from the published description, not stated by the maintainer.
What this server can do
13 functions, named and described by the server itself. Parameter names are shown because they say more about what a function does than its name usually does.
ai_search(prompt)- Natural-language semantic search powered by embeddings. Best for fuzzy intent ('a tool that helps me write Python tests', 'something like Midjourney but free'). Returns up to 12 apps ranked by semantic similarity. Required: prompt.
apps_for_audience(slug, limit, cursor)- Get the best AI tools for a specific audience by slug (from `list_audiences`), ranked by relevance then popularity. Use when the user asks 'best AI tools for {role/profession}'. Paginate with `cursor` (last app id from the previous page). Required: slug.
apps_for_use_case(slug, limit, cursor)- Get AI tools for a specific use case by slug (from `list_use_cases`), ranked by relevance then popularity. Use when the user asks 'AI tools for {task}'. Paginate with `cursor` (last app id from the previous page). Required: slug.
browse_apps(limit, cursor, letter, pricing)- Browse apps A-Z by starting letter. Use letter='#' for apps starting with digits or symbols. Useful for alphabetical discovery rather than search. Required: letter.
category_apps(slug, limit, cursor, pricing)- Get apps within a specific category. Returns the category metadata plus a paginated list of apps in that category, sorted by popularity. Required: slug.
get_alternatives(slug, limit)- Get curated alternatives to a specific AI app by slug. Returns the app plus a list of competing/similar tools ranked by match confidence. Use this when the user asks 'what are alternatives to X', 'something like X', or 'X vs others'. Required: slug.
get_app(slug)- Fetch the full detail page for a single AI app by slug: long description, features, screenshots, categories, pricing, rating, website URL, source attribution. Required: slug.
get_homepage(page)- Fetch the HyperStore homepage payload: top categories with their featured apps, the trending apps strip, and totals. Good first call to give the user a broad overview.
list_apps(limit, query, cursor, pricing, category)- Paginated apps listing with optional filters. Combine `category`, `pricing`, and a free-text `query` to drill down. Returns apps sorted by popularity. Use `cursor` (last app id from previous page) to paginate.
list_audiences- List the audience segments HyperStore curates tools for (e.g. 'developers', 'lawyers', 'students'), each with a slug and app count. Call this first to discover audience slugs for `apps_for_audience`.
list_categories- List all HyperStore categories with app counts. Use this first when the user asks 'what kinds of AI tools are there?' or to discover available category slugs.
list_use_cases- List the use-case taxonomies HyperStore curates tools for (e.g. 'legal-contracts', 'tiktok-shorts'), each with a slug and app count. Call this first to discover use-case slugs for `apps_for_use_case`.
search_apps(limit, query, cursor)- Search HyperStore's AI apps directory by keyword. Returns a paginated list of matching apps with name, slug, short description, pricing, and rating. Use this when the user gives concrete keywords (e.g. 'image upscaler', 'code copilot'). Required: query.
Last successful function declaration observed on . Source: https://mcp.store.hypergpt.ai/mcp. We list what the server declared; we do not call any of these functions.
Endpoint status observed on . Source: https://mcp.store.hypergpt.ai/mcp.
Signals
These are separate measurements of different things. They are deliberately not combined into one score, because a popularity number that mixes website traffic with saves and stars cannot be checked or acted on.
| Signal | Value | What it measures | Window | Observed | Source |
|---|---|---|---|---|---|
| GitHub stars | 1 | Number of GitHub accounts that bookmarked this repository since it was created. It is a bookmark count, not installs, not active users and not quality. | cumulative, all time | GitHub | |
| Last commit | 2026-06-20 | Date of the most recent push to any branch. This is the strongest cheap indicator of whether the project is still maintained. | point in time | GitHub | |
| Open issues | 0 | Open issues plus open pull requests, as GitHub counts them together. A high number can mean an active project or an abandoned one. | as of fetch | GitHub | |
| Latest published version | 0.1.1 | Latest version string the maintainer published to the registry. | as of fetch | Model Context Protocol | |
| Registry record last updated | 2026-05-16 | When the registry record was last updated by its maintainer. | point in time | Model Context Protocol | |
| License | MIT | Licence GitHub detected in the repository. Detection can be wrong; the LICENSE file is authoritative. | as of fetch | GitHub | |
| First listed in the MCP Registry | 2026-05-16 | Date this server was first published to the official MCP Registry. Not a usage or quality measure. | point in time | Model Context Protocol | |
| repository status | active | The repository exists on GitHub and is not archived. This says nothing about how recently it was worked on. | as of fetch | GitHub | |
| mcp tools declared | 13 tools | Number of functions the server itself declared when asked to list them. This is what the server offers an agent, not a measure of how well any of them work. | as of probe | mcp.store.hypergpt.ai | |
| mcp endpoint status | ok | The server listed 13 functions when asked. | as of probe | mcp.store.hypergpt.ai |
Where to get it
Also from deficlow
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This record as data
Every field on this page, with its source and observation date, is in the catalog JSON. Fetch the whole kind at once instead of parsing this HTML.
GET /api/v1/entries/mcp_server.json