mcpbeat

HyperStore MCP Server

io.github.deficlow/hyperstore-mcp
answering

HyperStore is answering right now. Last checked 3 min ago. 89 installs a week from pypi. It exposes 13 tools. Last commit 20 Jun 2026.

Search and inspect 6,500+ curated AI apps from the HyperStore directory.

Installs per day peak 31 · avg 14 · +17% w/w
a month agotoday
Uptime history 47 hours of history · worst hour 43%
47 hours agonow
50.0%
Uptime 24h
92 of 184 checks
13
Tools
read from the server
386 ms
Response time
average over 24h
89
Installs / week
npm and PyPI

Connect this server

Endpoint below is the one we actually reach during checks — not the one copied from a README. Last verified 3 min ago.

run in your terminal
claude mcp add hyperstore-mcp --transport http https://mcp.store.hypergpt.ai/mcp
~/Library/Application Support/Claude/claude_desktop_config.json
{
  "mcpServers": {
    "hyperstore-mcp": {
      "url": "https://mcp.store.hypergpt.ai/mcp"
    }
  }
}
~/.codex/config.toml
[mcp_servers.hyperstore-mcp]
url = "https://mcp.store.hypergpt.ai/mcp"
.cursor/mcp.json
{
  "mcpServers": {
    "hyperstore-mcp": {
      "url": "https://mcp.store.hypergpt.ai/mcp"
    }
  }
}
.vscode/mcp.json
{
  "mcpServers": {
    "hyperstore-mcp": {
      "url": "https://mcp.store.hypergpt.ai/mcp"
    }
  }
}

Available tools 13

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

apps
apps_for_audience
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).
apps_for_use_case
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).
list_apps
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.
search_apps
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').
ai
ai_search
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.
alternatives
get_alternatives
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'.
app
get_app
Fetch the full detail page for a single AI app by slug: long description, features, screenshots, categories, pricing, rating, website URL, source attribution.
audiences
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`.
browse
browse_apps
Browse apps A-Z by starting letter. Use letter='#' for apps starting with digits or symbols. Useful for alphabetical discovery rather than search.
categories
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.
category
category_apps
Get apps within a specific category. Returns the category metadata plus a paginated list of apps in that category, sorted by popularity.
homepage
get_homepage
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.
use
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`.

Endpoints

URLTransportStateLatencyChecked
https://mcp.store.hypergpt.ai/mcp streamable-http answering 360 ms 3 min ago
https://mcp.store.hypergpt.ai/sse sse answering 356 ms 3 min ago

HyperStore — questions

Answers built from our own checks of this server.

What can HyperStore do?
It exposes 13 tools, read directly from the server on our last check. Among them: ai_search, apps_for_audience, apps_for_use_case, browse_apps, category_apps, get_alternatives and 7 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 →
Is HyperStore working right now?
We send a real MCP handshake every 15 minutes. Over the last 24 hours 92 of 184 checks got a reply (50.0%), average response time 386 ms. The bar chart above shows every period we have measured.
How do I connect HyperStore?
Copy the ready config from this page — we generate it for Claude Code, Claude Desktop, Codex, Cursor and VS Code, each with the file path that client actually reads. It is a remote server, so there is nothing to install — the client connects to the address.
Does HyperStore need an API key?
No. HyperStore completed a full MCP handshake with us as an anonymous client and listed its tools without asking for anything. All 13 of them are readable on this page. This is what we observed, not what the docs claim.
How fast is HyperStore?
It answers our handshake in 386 ms on average, which is faster than 36% of all working MCP servers we measure. The comparison comes from our own checks across the whole registry, every 15 minutes.
How many people use HyperStore?
The pypi package hyperstore-mcp was installed 89 times in the last week. Week over week that is +17%. We show installs rather than GitHub stars on purpose: a star is a bookmark, an install is someone actually running it.
Is HyperStore open source?
Yes — it is published under the MIT licence, written in Python and 1 stars on GitHub. The source link is on this page, so you can read exactly what it does with your data before you connect it.